Contemporary Management Research - CiteSeerX

Contemporary Management Research Vol. 1, No.1, September 2005 ISSN:1813-5498

Contents Consumer Complaining Behavior: The Case of a South American Country, Chile

3

Fredy Valenzuela, David Pearson, Roger Epworth, Orlando Llanos, and Sonia Vilches

Internet-Enabled Mobile Handheld Devices for Mobile Commerce

13

Wen-Chen Hu, Jyh-haw Yeh, Hung-Ju Chu, and Chung-wei Lee

Technological Innovativeness and Organizational Culture in Hong Kong

35

Gary Y. F. Wong and Richard Y. K. Fung

How do Organizations Implement Downsizing? – An Australian and New Zealand Study

57

Franco Gandolfi

The Role of Personality Traits in UTAUT Model Under Online Stocking Hsing-I Wang and Heng-Li Yang

69

Contemporary Management Research Vol. 1, No.1, September 2005 ISSN:1813-5498 Publisher: Academy of Taiwan Information Systems Research Editor: Wenchang Fang

National Taipei University

“Contemporary Management Research” Editorial Board Namjae Cho Hanyang University, Korea Ergun Gide Central Queesland University, Australia Wen-Chen Hu University of North Dakota, United Status Ta-Wei Hung Shih Chien University, Taiwan J.A.S.K. Jayakody University of Colombo, Sri Lanka Nihat Kasap Sabanci University, Turkey Hemant Kassean University of Mauritius, Mauritius Yacov Kedem Shenkar College of Engineering and Design, Israel Fumikatsu Kubo Chuo University, Japan Yikuan Lee San Francisco State University, United States Ting Lie Yuan Ze University, Taiwan Jinsan Lin Nagoya Sangyo University, Japan Xiaohua Lin University of Windsor, Canada Iraj Mahdavi Mazandaran University of Science and Technology, Iran Guillermo Rodriguez-Abitia ITESM Campus Estado de Mexico, Mexico Beh Loo See University of Malaya, Malaysia Ushio Sumita University of Tsukuba, Japan Muhammad Suryanegara University of Indonesia, Indonesia Chih-Chien Wang National Taipei University, Taiwan Chian-Son Yu Shin Chien University, Taiwan (Ranked by last names) Editorial Assistant: Yi-Lei Chang Editorial office: P. O. Box 179-45, Taipei City 116, Taiwan Website: http://cmr.atisr.org E-mail: [email protected] Fax:+886-2-2517-5924

Contemporary Management Research Pages 3-12,Vol.1, No.1, September 2005

Consumer Complaining Behavior: The Case of a South American Country, Chile Fredy Valenzuela University of New England, Australia, and University of Talca, Chile E-mail: [email protected]. David Pearson University of New England, Australia E-Mail: [email protected] Roger Epworth University of New England, Australia E-Mail: [email protected] Orlando Llanos Universidad Católica de la Santísima Concepción, Chile E-Mail: [email protected] Sonia Vilches Universidad Católica de la Santísima Concepción, Chile E-Mail: [email protected]

ABSTRACT Complaining behaviour is a topic that has not been studied much in South America. Considering this, the aim of this investigation was to determine the customers complaining behaviour of a South American country, Chile. To do so, a survey was done, which was applied to a random sample of 498 Chileans. Results show that Chileans do not consider complaining as a right, they have a regular opinion of the way companies are handling complaints, and that the product characteristics is the dimension that has the biggest influence on their complaining behaviour. In addition those Chilean consumers who have complained in the past have a more positive attitude toward complaining than those who have never done it. Key Words: Complaining, Consumer Behaviour, South America, Chile

Contemporary Management Research 4

INTRODUCTION In an ideal world, when consumers are dissatisfied they would immediately speak up so firms would have the opportunity to respond immediately by improving the quality of their services. However, not many people complain, so firms do not know that they are incurring in a service failure. Based on this, it is evident that failure in management is not necessarily through having a high percentage of consumer complaints to deal with (Zairi, 2000), rather firms should encourage consumers to speak up every time they are dissatisfied (Barlow and Moller, 1996:26). One aspect in which there is consensus among researchers is the fact that not all consumers engage in some of complaint action. In this line, Andreassen (2001) mentioned that the number of consumers who complain is lower that of those who do not complain. Chakrapani (1998:12) suggested that only 4% of dissatisfied consumers complain, and this is due to different reasons, which are: a) consumers might not know to whom to complain, b) negative experiences related to having their complaints handled poorly, and c) consumer belief that complaining is an exercise in futility because they will be either ignored or patronized. In general, these reasons can be categorized coming from two sources: company attitude toward responses to complaints and consumer attitude toward complaining. The latter is the personal tendency of dissatisfied costumers to seek compensation from the firm (Beardon and Mason, 1984). Several studies have been done to cover different issues related to consumers complaining behaviour however a very important issue that has not been addressed in the literature is the situation of developing countries, and in particular South American countries. There are only few studies that focus on consumer complaining behaviour, such as Valenzuela (1999) and Valenzuela et al. (2002a; 2002b), but all them give only an overall picture of Chileans complaining behaviour, covering aspects such as percentage of consumers who complain and gender and social class differences. Due to this, firms in these countries have to use information gathered in a totally different setting to make decisions as to the design mechanisms for encouraging consumers to speak up every time they are dissatisfied with what have purchased. Considering this, this study aims to gather information regarding Chilean consumers complaining behaviour. LITERATURE REVIEW Barlow and Moller (1996:43) presented the results of study done by the Case Western Reserve University, in which interviewed dissatisfied consumers fell into four clusters and were identified as voicers (37%), passives (14%), irates (21%), and activists (28%). Voicers will tell the company that something is wrong, passives will not say anything and will remain purchasing from their suppliers at least for a while, irates will not say a word to the firms but they will engage in negative word of mouth, and activists more than redress, they look for revenge. Regarding the variables that influence consumers complaining behaviour, several studies have shown that there is a relationship between complaining and demographic variables, psychographic variables (e.g. consumer personality and attitude toward firms) and product characteristics. Demographic variables have been subject of attention and different conclusions have been obtained by different researchers. For instance, Keng et al. (1995) and Heung and Lam (2003) concluded that female consumers are more inclined to complain, while Manikas and Shea (1997) findings show totally the opposite. Relative to the role of education, research has shown that


there is a direct relationship between level of education and complaining (Beardon and Mason, 1984; Day and Lando, 1977; Heug and Lam, 2003; Jacoby and Jaccard, 1981; Morganosky and Buckely, 1986). In relation to psychographic factors, such as personality and attitude, Davidow and Dacin (1997) concluded that these factors are the major reasons of complaint behaviour. In the same line, other researchers have concluded that consumers who complain are more social responsible and willing to take risks such as the risk of embarrassment when complaining (Fornell and Westbrook, 1979; Keng et al., 1995; Lau and Ng, 2001). If differences between complainers and non-complainers are considered, non-complainers considered that complaining was done by people with little else to do and it would be futile (Keng et al., 1995). Concerning attitude toward firms, several researchers have concluded that there is a positive relationship between responsiveness and complaining (Keng et al., 1995; Lau and Ng, 2001; Richins and Verhage, 1985). Sometimes consumers are discouraged from speaking up by negative complaint handling procedures, such as simple apologies and nothing more, rejection (verbal or non verbal), promises that are not acted upon, no response at all, rude treatment, being passed on to someone else, employees who avoiding personal responsibility or consumer interviews that turn into interrogations (Barlow and Moller, 1996:59-61). With regard to the relationship between product characteristics and complaining behaviour, Day and Lando (1977) and Keng et al. (1995) concluded that is more likely for consumer to complain if the product is not performing as promised and this situation can have a negative impact on their image of the firm. It was also demonstrated that there is a direct relationship between price and complaining behaviour, meaning that consumer will engage in complaining behaviour if the product they are dealing with is more expensive. METHODOLOGY The main method used in this study was a survey. To do so, a questionnaire was designed, which was in Spanish and had open-ended and close-ended questions. The first ones were used to allow respondents to give a description of the situation that provoked the complaint. Closeended questions were used to gather data related to the Chilean consumers complaining behaviour, which in this study was divided in four dimensions: a) Consumer Personality, b) Consumer Social Responsibility, c) Product Characteristics, and d) Attitude toward firms. To measure these dimensions, scale items used in other research were used, but with some small modifications to adapt them to the Chilean context (Keng et al., 1995; Phau and Puspita Sari, 2004). These scale items were translated to Spanish by the researcher, and the translation was checked by two Chilean Marketing Research Professors, so to ensure that the translation was appropriate. Table 1 show examples of scale items used in this investigation.


Table 1 Example of Scales Items Used to Measure Consumer Attitude toward Complaining Dimension Consumer Personality Consumer Social Responsibility Product Characteristics Attitude Toward Firms

Scale Item I find it embarrassing to complain Complaining about an unsatisfactory product is my duty The more frequently I have to use the product, the more likely I am to complaint if it is faulty Firms are usually willing to provide repairs for faulty products

Concerning sampling and because it is intended to get data related to complaint issues, it was key to interview people who have had a bad purchase experience, this means, they have been dissatisfied with what they bought. Due to this, the question ‘have you ever been dissatisfied with the product/service you purchased?’ was included in the questionnaire, and all people who answered ‘no’ were dropped from the study. The exploratory research consisted in a survey that was applied to 498 Chileans. It also important to mention that from those 498 consumers, 98 or 20% indicated that they have never been dissatisfied with the product or service they got from a supplier. From the rest (n=400), 317 or 79% mentioned to have complained in the past (See Figure 1). 20%

Satisfied

Total Sample

80%

79%

Complainers

21%

NonComplainers

Dissatisfied

Figure 1 Sample Data Distribution

Regarding data analysis, several approaches were used in order to check validity and reliability. First factor analysis was done using Varimax Rotation. To check reliability of each factor Alfa Cronbachs were calculated. Then Confirmatory Factory analysis was done using AMOS 5.0 MAIN FINDINGS Main finding were divided into four: a) Complaints per Industry, b) Consumer Complaining Behaviour Construct, c) Overall Results for each Consumers Complaining Behaviour Dimension, and d) Influence of a Series of Variables on Consumers Complaining Behaviour Complaints per Industry As can be seen in Table 2, the industry that got most complaints was the department store category with a 31.4% of all complaints followed by specialist stores with 30.5% of all complaints, supermarkets 10.2%, telephone industry with 6.3%, and bank industry with 5.7%.


Table 2 Complaints per Industry Type Industry Department Store Specialist Store Supermarkets Telephone Banks Transport Others

Percentage 31.4% 30.5% 10.2% 6.3% 5.7% 3.8% 12.1%

Regarding data analysis, this was divided into three types: 1) validity and reliability of the construct “Consumer Complaining Behaviour”, 2) overall results for each dimension considered in this study, and 3) Influence of several variables (e.g. gender, social class, city and complainer or non complainer) on consumers complaining behaviour. Consumer Complaining Behaviour Construct Four factors resulted from factor analysis, each of them with three scale items. The lodging values of the scales items in their respective factor went from 0.60 to 0.80. Regarding reliability, Alfa Cronbachs were not very high ranging from 0.57 and 0.65. In relation to the total explained variance this was only 59% (See Table 3). Regarding the meaning of each factor, the first one represents the consumer’s personality affecting complaining, the second one consumer’s social responsibility, the third one is related to product characteristics affecting consumer complaining behaviour, and the last one to consumer’s attitude toward the way firms handle complaints. Table 3 Consumer Complaining Behaviour Construct: Factor Analysis

Consumer Personality 1 Consumer Personality 2 Consumer Personality 3 Consumer Social Resp.1 Consumer Social Resp.2 Consumer Social Resp.3 Product Characteristics 1 Product Characteristics 2 Product Characteristics 3 Attitude toward firms 1 Attitude toward firms 2 Attitude toward firms 3 Reliability Explained Variance Accumulate Variance

Consumer personality 0.61 0.78 0.71

Consumer Social Responsibility

Product characteristics

Attitude toward firms

0.80 0.75 0.60 0.75 0.76 0.79

0.57 15% 15%

0.59 14.6% 29.6%

0.65 14.5% 44.3%

0.71 0.80 0.75 0.64 14.2% 58.5%


To further validate these dimensions, confirmatory factor analysis was done, using the software AMOS 5.0. The values of all goodness of fit indexes are very good (e.g. GFI, AGFI and CFI are above 0.9 and RMSEA below 0.8) confirming the existence of a multidimensional structure in the sample data. The values obtained in this analysis can be observed in Table 4 Table 4 Confirmatory Factor Analysis Goodness of Fit Indexes Goodness of fit Index GFI AGFI CFI RMSEA Chi-Square Degree of Freedom Chi-Square to Degree of Freedom ratio

Value 0.96 0.94 0.92 0.05 [0.039-0.068] 102.114 48 2.12

Overall Results for each Consumers Complaining Behaviour Dimension Regarding the four dimensions considered in this study, only one of them got a high mean, two of them were in the average and one of them got a very low score (See Table 5). The dimension ‘product characteristics’ got a high score, meaning that Chilean consumers complaining behaviour depends on the characteristics of the product. If the product is considered important for them it is very likely that they will complain. The dimension ‘attitude toward firms’ got a regular score, meaning that Chilean consumer believe that Chilean companies do not care for solving their complaints so it would be a wasted of time engage in a complaining behaviour. The dimension ‘consumer personality’ got also a regular score, meaning that Chilean consumers see themselves as passive people regarding complaining. Regarding the last dimension, consumers’ social responsibility, this dimension got the lowest score, meaning that Chilean do not see complaining as a right or/and as an obligation. Table 5 Chilean Consumer Complaining Behaviour Means Product Characteristics Consumers’ Personality Attitude toward firms Consumers’ Social Responsibility

Mean 4.32 3.35 3.30 2.33

Standard Deviation 0.71 0.99 0.97 0.89

Influence of a Series of Variables on Consumers Complaining Behaviour In order to further understand the behaviour of Chilean consumers, several additional analyses were done with the aim of comparing the attitude score obtained by different variables, such as gender and type of complainer. The main findings are show next. Gender Differences The percentage of women and men who have complained to the supplier is very high, 78.4% and 80%, respectively. The difference between these two percentages is not statically significant. It is important to mention that this result does not mean that every time that they are


dissatisfied these consumers have complained, it is just saying that they have done it at least once. Regarding the four dimensions considered in this study, the main results of this analysis can be seen in Table 6. In this Table is very clear that there is almost no difference in the answers of men and women. The only aspect that differs in the latter is the social responsibility aspect in where men scored higher than women, meaning that they are much more social responsible than women. Table 6 Difference between Men and Women Consumers’ Social Responsibility Consumers’ Personality Product Characteristics Attitude toward firms

Mean Difference 0.350 0.001 -0.109 -0.110

Significance 0.000 0.875 0.131 0.260

Social Class To determine if there is any difference among social class, ANOVA analysis was done, which shows no statistical difference among the attitude of consumers belonging to the low, medium and upper class (see Table 7). This conclusion was further supported by the fact that there is no statistical difference in the percentages of consumers from upper, medium and low social classes who have complained at least once in the past. These percentages are 81%, 77% and 83%, respectively. Table 7 ANOVA for difference among Social Class Consumers’ Personality Consumers’ Social Responsibility Product Characteristics Attitude toward firms

F 0.197 0.950 0.787 2.235

Significance 0.821 0.388 0.456 0.108

Complainers versus non Complainers In order to determine if there is any difference in the attitude regarding complaining of consumers who have complained in the past versus those who have never done it, mean differences were calculated for each of the four dimensions of the consumer complaining behavior. Results show statistical differences in the mean of three of the four dimensions, these being consumers’ personality, consumers’ social responsibility and the influence of the product characteristics. The only dimension that shows no significant difference is attitude toward firms, meaning that complainers and non complainers have a similar perception regarding the attitude that firms have for solving complaints. Table 8 shows the main results of this analysis.


Table 8 Difference between Complainers and Non-Complainers Consumers’ Personality Consumers’ Social Responsibility Product Characteristics Attitude toward firms

Mean Difference +1.005 +0.340 +0.411 +0.001

Significance 0.000 0.001 0.000 0.916

CONCLUSIONS Several conclusions can be obtained from this study. The first one is the validity of the four dimensions to measure consumers complaining behavior. In this study results of the confirmatory factor analysis were excellent which further reaffirm the existence of this multidimensional structure. Regarding Chileans’ complaining behavior it was determined that there are several aspects that are negatively influencing their behavior. It seems that Chilean are more likely to complain when the product that is in involved in the complaint situation has attributes that are considered important for the consumer, such as, high price, long-term expectancy life, or a product that they use often. In relation to the way firms are handling complaints Chilean consumers have a regular opinion of the willingness of these firms for handling their complaints in a proper way. This could imply that Chilean consumers may not be willing to speak up when they are dissatisfied with the product, because they will consider it a waste of time and energy. The other dimensions considered in this study consumer personality shows also a medium score, meaning that Chilean feel some how embarrass when complaining, and if this characteristics is added to the fact that Chilean do not consider complaining as a right or social responsibility, it might lead to low rate of consumers complaints. Relative to some variables that might influence the consumer complaining behavior, there is evidence that gender and social class are not relevant in this matter, which is different from those conclusions made in other research (Keng et al., 1995; Phau and Puspita, 2004). The variable that shows a statistical difference in consumers complaining behavior is the type of complainer. Active complainers have a more positive attitude while passive or noncomplainers have a more negative attitude toward complaining. This result is in line with what was concluded by Chulmin et al. (2003) regarding that is more likely that consumers who have a more positive attitude toward complaining will engage in such a behavior. All these conclusions have very important managerial implications. Firms that want to increase the number of consumers who complain when they are dissatisfied should: a) Focus on consumers who are active complainers, who are not defined by gender of social class. The reason for this is because it would be more likely to achieve a greater impact from these consumers, because they have a positive attitude toward complaining.


b) Have in place mechanisms for handling complaints otherwise the consumers will increase their negative perception regarding the attitude that firms have to solve complaints. LIMITATIONS The main limitation of this investigation is the ability to generalize its conclusions, mainly because all data were gathered only in two Chilean cities, and hence there is the opportunity for validation of its conclusions in other Chilean cities and other South American countries. REFERENCES Andreassen, T. W. (2001). From disgust to delight: Do customers hold a grudge? Journal of Service Research : JSR, 4(1), 39. Barlow, J., & Moller, C. (1996). A Complaint is a Gift. San Francisco: Berrett-Koehler Publishers. Beardon, W., & Mason, J. (1984). An investigation of influences on consumer complaint reports. In T. Kinnear (Ed.), Advances in Consumer Research (Vol. 11). Chakrapani, C. (1998). How to Measure Service Quality & Customer Satisfaction. Chicago: Amercian Marketing Association. Chulmin, K., Sounghie, K., Subin, I., & Changhoon, S. (2003). The effect of attitude and perception on consumer complaint intentions. Journal of Consumer Marketing, 20(4), 352371. Davidow, M., & Dacin, P. (1997). Understanding and influencing consumer complaint behaviour: improving organizational complaint management. Advances in Consumer Research, 24. Day, R., & Lando, E. (1977). Toward a theory of consumer complaint behaviour. In W. e. al. (Ed.), Consumer and Industrial Buying Behaviour. New York: North Holland. Fornell, C., & Westbrook, R. (1979). An exploratory study of assertiveness and consumer complaining behaviour. Advances in Consumer Research, 6, 105-114. Heug, V., & Lam, T. (2003). Customer complaint behaviour towards hotel restaurants services. International Journal of Contemporary Hospitality Management, 15(5), 283-289. Jacoby, J., & Jaccard, J. (1981). The sources, meanings and validity of consumer complaint behaviour: a psychological analysis. Journal of Retailing, 57(3), 4-24. Keng, K., Richmond, D., & Han, S. (1995). Determinants of consumer complaint behaviour: a study of Singapore consumers. Journal of International Consumer Marketing, 8(2), 59-76. Lau, G., & Ng, S. (2001). Individual and situational factors influencing negative work of mouth behaviour. Revue Canadienne des Sciences de l'Administration, 18(3), 163-178. Manikas, P., & Shea, L. (1997). Hotel complaint behaviour and resolution: a content analysis. Journal of Travel Research, 36(2), 68-73. Morganosky, M., & Buckely, H. (1986). Complaint behaviour: analysis by demographics, lifestyle and consumer values. Advances in Consumer Research, 14, 223-226. Phau, I., & Puspita, R. (2004). Engaging in complaint behaviour : An Indonesian perspective. Marketing Intelligence and Planning, 22(4), 407-426. Richins, M., & Verhage, V. (1985). Seeking redress for consumer dissatisfaction: the role of attitudes and situational factors. Journal of Consumer Policy, 18(1), 29-44.


Valenzuela, F. (1999). Consumer Complaining Behavior: The Chilean Situation. Paper presented at the CLADEA, San Juan, Puerto Rico. Valenzuela, F., Silva, R., & Valdes, V. (2002a). Comparative Study of Chilean and German Consumers Profiles and Effects of an Ineffective Management of Complaining. Documents of Economy and Administration, 4, 16-18. Valenzuela, F., Silva, R., & Valdes, V. (2002b). Consumer Complaining Behavior: Comparative Study of Chilean and German Consumers. Panorama Socioeconomico, 24, 36-40. Zairi, M. (2000). Managing Customer Dissatisfaction Through Effective Complaints Management Systems. The TQM Magazine, 12(5), 331-335.


Internet-Enabled Mobile Handheld Devices for Mobile Commerce Wen-Chen Hu University of North Dakota E-Mail: [email protected] Jyh-haw Yeh Boise State University E-Mail: [email protected] Hung-Ju Chu University of Florida E-Mail: [email protected] Chung-wei Lee Auburn University E-Mail: [email protected]

ABSTRACT The emergence of wireless and mobile networks has made possible the introduction of electronic commerce to a new application and research area: mobile commerce. Internet-enabled mobile handheld devices are one of the core components of a mobile commerce system, making it possible for mobile users to directly interact with mobile commerce applications. Much of a mobile user’s first impression of the application will be formed by his or her interaction with the device, therefore the success of mobile commerce applications is greatly dependent on how easy they are to use. This article first explains the role of handheld devices in mobile commerce systems and then discusses the devices in detail. A mobile handheld device includes six major components: i) a mobile operating system, ii) a mobile central processor unit, iii) a microbrowser, iv) input/output devices, v) a memory, and vi) batteries. Each component is described in detail and major products and technologies for the component are given. The technology needed for synchronization with desktop PCs and various mobile commerce applications is also presented. Key words: Mobile Commerce, Internet INTRODUCTION With the introduction of the World Wide Web, electronic commerce has revolutionized traditional commerce and boosted sales and exchanges of merchandise and information. Recently, the emergence of wireless and mobile networks has made possible the extension of electronic commerce to a new application and research area: mobile commerce, which is defined as the exchange or buying and selling of commodities, services, or information on the Internet


through the use of mobile handheld devices. In just a few years, mobile commerce has emerged from nowhere to become the hottest new trend in business transactions. Despite a weak economy, the future of mobile commerce is bright according to the latest predictions:

Figure 1 Forecast of demand for mobile handheld computing devices •

•

•

Figure 1 shows the growth in demand for handheld computing devices (not including smart cellular phones) through 2007, as predicted by the research firm In-Stat/MDR (PalmInfocenter.com, 2003). It is estimated that 50 million wireless phone users in the United States will use their handheld devices to authorize payment for premium content and physical goods at some point during the year 2006. This represents 17 percent of the projected total population and 26 percent of all wireless users (Reuters, 2001). Mobile commerce is an effective and convenient way of delivering electronic commerce to consumers from anywhere and at any time. Realizing the advantages to be gained from mobile commerce, companies have begun to offer mobile commerce options for their customers in addition to the electronic commerce they already provide (The Yankee Group, 2002).

A mobile commerce system involves a variety of components, among which mobile handheld devices feature largely as they provide the equipment mobile users need to interact with mobile commerce applications. Therefore, much of a mobile user’s first impression of the application comes from how easy the devices are to use. The success of mobile commerce applications is thus greatly dependent on the devices. This paper discusses mobile handheld devices and their role in mobile commerce. A handheld device includes six major components: i) a mobile operating system, ii) a mobile central processing unit, iii) a microbrowser, iv) input/output devices, v) a memory, and vi) batteries. The six components, along with synchronization with desktop PCs and peripherals, are described in detail and their related technologies and products are introduced. Mobile commerce applications are also discussed.


Requirements of a Mobile Handheld Device It is first necessary to examine which of features a handheld device is expected to have in order to conduct effective and efficient mobile commerce transactions and the challenges that must be overcome in the process of developing new mobile handheld devices. The requirements for a mobile handheld device are: • It should be small enough to be held in one hand. • Input methods must be easy to use and learn. • The screen must be large enough for mobile users to read the contents effortlessly and use the stylus without difficulty. • Processors should be powerful enough to process users’ requests with short latencies, while at the same time consuming less power to lengthen the battery life. • Maximum interoperability is desirable because many technologies are now available for handheld devices and new techniques are constantly being introduced. • The memory must be large enough for most mobile commerce applications. • Battery life must be sufficient for operations lasting several hours before the batteries need to be recharged. • Synchronization with desktop PCs or peripherals should be convenient and easy. MOBILE COMMERCE SYSTEMS Internet-enabled mobile handheld devices play a crucial role in mobile commerce, as they are the devices with which mobile users interact directly with mobile commerce applications. This section first introduces a mobile commerce system and then illustrates how it is used to carry out a mobile transaction. System Structure A mobile commerce system is inherently interdisciplinary and could be implemented in various ways. Figure 2 shows the structure of a mobile commerce system and a typical example of such a system (Hu, Lee, & Yeh, 2003). The system structure includes six components: i) mobile commerce applications, ii) mobile handheld devices, iii) mobile middleware, iv) wireless networks, v) wired networks, and vi) host computers. 1. Mobile commerce applications: Electronic commerce applications are numerous, including auctions, banking, marketplaces and exchanges, news, recruiting, and retailing, to name but a few. Mobile commerce applications not only cover the electronic commerce applications, but also include new applications, which can be performed at any time and from anywhere by using mobile computing technology, for example, mobile inventory tracking. 2. Mobile handheld devices: An Internet-enabled mobile handheld device is a small generalpurpose, programmable, battery-powered computer that is capable of handling the front end of mobile commerce applications and can be operated comfortably while being held in one hand. It is the device with which mobile users interact directly with mobile commerce applications. 3. Mobile middleware: The term middleware refers to the software layer between the operating system and the distributed applications that interact via the networks. The primary mission of a middleware layer is to hide the underlying networked environment's complexity by


insulating applications from explicit protocols that handle disjoint memories, data replication, network faults, and parallelism (Geihs, 2001). The major task of mobile middleware is to seamlessly and transparently map Internet contents to mobile stations that support a wide variety of operating systems, markup languages, microbrowsers, and protocols. WAP and imode are the two major kinds of mobile middleware. According to an article in Eurotechnology.com (Eurotechnology Japan K. K., 2002), 60 percent of the world’s wireless Internet users use i-mode (NTT DoCoMo, n.d.), 39 percent use WAP (Wireless Application Protocol Forum Ltd., n.d.), and 1 percent use Palm middleware. Table 1 compares i-mode and WAP. 4. Wireless and wired networks: Wireless communication capability supports mobility for end users in mobile commerce systems. Wireless LAN, MAN, and WAN are the major components used to provide radio communication channels so that mobile service is possible. In the WLAN category, the Wi-Fi standard with 11 Mbps throughput dominates the current market. However, it is expected that standards with much higher transmission speeds, such as IEEE 802.11a and 802.11g, will replace Wi-Fi in the near future. Compared to WLANs, cellular systems can provide longer transmission distances and greater radio coverage, but suffer from the drawback of much lower bandwidth (less than 1 Mbps). In the latest trend for cellular systems, 3G standards supporting wireless multimedia and high-bandwidth services are beginning to be deployed. 5. Host computers: A user request such as database access or updating is actually processed at a host computer, which contains three major kinds of software: i) Web servers, ii) database servers, and iii) application programs and support software. Table 1 Comparisons of the two major types of mobile middleware WAP

i-mode

Developer

WAP Forum

NTT DoCoMo

Function

A protocol

A complete mobile Internet service

Host Language

WML (Wireless Markup Language)

CHTML (Compact HTML)

Major Technology

WAP Gateway

TCP/IP modifications

Key Features

Widely adopted and flexible

Highest number of users and easy to use


Users MC applications

Users User interface

Mobile devices

Internet-enabled PDAs

Mobile middlew are

WAP

Wireless netw orks

Wireless LAN

Wired netw orks

Wired LAN/WAN

Host computers

Host computers

Web servers

MC application programs

Database servers Databases Databases

An MC System Structure

association bidirectional data/control flow optional component

A Typical Implemention

Figure 2 A mobile commerce system structure An Example of Mobile Commerce Transaction Processing To explain how the mobile commerce components work together, Figure 3 shows a flowchart of how a user request is processed by the components in a mobile commerce system, along with brief descriptions of how each component processes the request.


Figure 3 A flowchart of a user request processed in a mobile commerce system

1. Mobile commerce applications: A content provider implements an application by providing two sets of programs: client-side programs, such as user interfaces on microbrowsers, and server-side programs, such as database access and updating. 2. Mobile handheld devices: Handheld devices present user interfaces to the mobile end users, who specify their requests on the interfaces. The devices then relay the user requests to the other components and later display the processing results using the interfaces. 3. Mobile middleware: The major purpose of mobile middleware is to seamlessly and transparently map Internet contents to mobile stations that support a wide variety of operating systems, markup languages, microbrowsers, and protocols. Most mobile middleware also encrypts the communication in order to provide some level of security for transactions. 4. Wireless networks: Mobile commerce is possible mainly because of the availability of wireless networks. User requests are delivered to either the closest wireless access point (in a wireless local area network environment) or a base station (in a cellular network environment). 5. Wired networks: This component is optional for a mobile commerce system. However, most computers (servers) usually reside on wired networks such as the Internet, so user requests are routed to these servers using transport and/or security mechanisms provided by wired networks. 6. Host computers: Host computers process and store all the information needed for mobile commerce applications, and most application programs can be found here. They include three major components: Web servers, database servers, and application programs and support software. MOBILE HANDHELD DEVICES Mobile users interact with mobile commerce applications by using small wireless Internetenabled devices, which come with several aliases such as handhelds, palms, PDAs, pocket PCs,


and smart phones. To avoid any ambiguity, a general term, mobile handheld devices, is used in this article. Mobile handheld devices are small general-purpose, programmable, battery-powered computers, but they are different from desktop PCs or notebooks due to the following special features: • Limited network bandwidth, • Small screen/body size, and • Mobility. Short battery life and limited memory, processing power, and functionality are additional features, but these problems are gradually being solved as the technologies improve and new methods are constantly being introduced. The limited network bandwidth prevents the display of most multimedia on a microbrowser. Though the Wi-Fi and 3G networks go some way toward addressing this problem, the wireless bandwidth is always far below the bandwidth of wired networks. The small screen/body size restricts most handheld devices to using a stylus for input. Figure 4 shows a typical system structure for handheld devices, which includes the following six major components: i) a mobile operating system, ii) a mobile central processing unit, iii) a microbrowser, iv) input/output devices, v) a memory, and vi) batteries. Brief descriptions of all the components follow, with more details in the next sections.

Data Mobile users

I/O devices

Wireless adapter

Instructions I/O bus

System bus Mobile CPU

Mobile OS

I/O bridge

Microbrowser

Memory bus Memory

Batteries

Figure 4 System structure of mobile handheld devices 1. Mobile operating systems: They are the core software of handheld devices. Mobile operating systems are different from those in desktop computers as they include the following additional features: i) power management to prolong the battery life, ii) real-time capability for time-critical operations such as voice communication, and iii) wireless infrastructure for wireless communication. 2. Mobile central processing units: Mobile CPUs are the core hardware of mobile handheld devices and the performance and functionality of the devices are heavily dependent on the capabilities of the processors.


3. Microbrowsers: Microbrowsers are Internet browsers specifically designed for use in mobile handheld devices. They differ from desktop browsers in several ways, specifically the languages they use, security, footprint, and smaller windows. The last feature, smaller windows, enables them to provide simplified interfaces, although it also eliminates much of the desktop browser's multimedia functionality, such as streaming -audio and -video support. 4. Input/output devices: There is only one major output device, the screen, but there are several popular input devices, in particular keyboards and touch screens/writing areas that require the use of a stylus. 5. Memory: Three types of memory are usually employed by handheld devices: i) random access memory, ii) read-only memory, and iii) flash memory. 6. Batteries: Rechargeable Lithium Ion batteries are the most common batteries used by handheld devices. Major Devices Mobile handheld devices are usually divided into two types: Figure 5 Sony Ericsson® P800 •

Smart cellular phones: They are voice-based devices with data-processing capability. An example is the Sony Ericsson P800, shown in Figure 5, which is basically a cellular phone with a built-in camera, speakerphone, Bluetooth and IR connectivity, wireless e-mail and Internet access, and MP3 audio and MPEG-4 video capability. It can be synchronized with Microsoft Outlook via the included USB docking station.

•

PDAs (Personal Digital Assistants): In contrast to smart cellular phones these are data-based devices, although they usually also have voice capability. Advanced PDAs provide the functions of telephone/fax, e-mails, PIM (personal information managers) such as calendars and address books, and networking features. A typical example is the Palm Tungsten C, shown in Figure 6, which includes features such as built-in Wi-Fi, an integrated keyboard, email and Internet access, a transflective screen, and a 400 MHz processor.

Figure 6 Palm® Tungsten C

These two kinds of devices started out as very different products, but they have gradually blended into each other. In the near future, it will be difficult to tell the difference between these two types of device. The newest products such as tablet PCs belong to the category of PDAs because both have similar functionality.


There are numerous mobile devices available in the market today. Table 2 lists some major mobile device specifications, although several table entries are incomplete as some of the information is classified as confidential due to business considerations.

Table 2 Specifications of some major mobile handheld devices Vendor & Device

Operating System

Processor

Compaq iPAQ H3870

MS Pocket PC 2002

Handspring Treo 300

Palm OS 3.5.2H

206 MHz Intel StrongARM 32-bit RISC 33 MHz Motorola Dragonball VZ

Motorola Accompli 009

Wisdom OS 5.0

Nokia 9290 Communicator

Symbian OS

Nokia 6800

Series 40

Palm i705

Palm OS 4.1

33 MHz Motorola Dragonball VZ

Samsung SPHi330

Palm OS 4.1

66MHz Motorola Dragonball Super VZ

Sony Clie PEGNR70V

Palm OS 4.1

66 MHz Motorola Dragonball Super VZ

MS Pocket PC 2002

Input Methods

Key Features

64 MB/32 MB

Touchscreen

Wireless email/Internet

16 MB/8 MB

Keyboard/ Stylus

CDMA network

33 MHz Motorola Dragonball VZ

8 MB/4 MB

Keyboard

GPRS network

32-bit ARM9 RISC

16 MB/8 MB

Keyboard

WAP

Keyboard

Innovative keyboard integration

8 MB/4 MB

Stylus

Wireless Email/Internet

16 MB/8 MB

Touchscreen/ Stylus

Color screen

16 MB/8 MB

Keyboard/ Stylus/ Touchscreen

Multimedia

800KB

Keyboard

Multimedia Messaging Service

64 MB/32 MB

Stylus/ Touchscreen

Wireless Internet

Sony Ericsson T68i Toshiba E740

Installed RAM/ROM

400 MHz Intel PXA250

MOBILE OPERATING SYSTEMS Simply adapting desktop operating systems for mobile handheld devices has proved to be a futile endeavor; an example of this effort is Microsoft Windows CE. A mobile operating system needs a new architecture and different features in order to provide adequate services for handheld devices. This section presents a mobile operating system structure and discusses some major systems.


System Structure Several mobile operating systems are already available and each employs a different architecture and implementation. Figure 7 shows a generalized mobile operating system structure, which can be visualized as a six-layer stack:

1. Applications 2. Graphical user interface (GUI) 3. Application programming interface (API) framework 4. Multimedia

Communication infrastructure

Security

5. Computer kernel

Power management

Real-time kernel

6. Hardware controller

Figure 7 A generalized mobile operating system structure

1. 2. 3.

4.

Mobile applications: This level refers to customer-level applications such as microbrowsers and mobile retailing. Details of various mobile applications will be given in a later section. Graphical user interface (GUI): Applications use the API to display information on the GUI, which is more limited in a mobile operating system than the GUI in a desktop OS. Application programming interface (API) framework: This level provides the framework between the low-level architecture components and the application layer. By using this framework, application developers do not need to know the underlying low-level details in order to take full advantage of their capabilities. This level consists of three components:

Contemporary Management Research 23 •

5.

6.

Multimedia: Widely adopting multimedia is one of the reasons for the success of electronic commerce. The same can be applied to mobile commerce, in particular more and more smart cellular phones are equipped with cameras. This module involves image/video related functionality, audio recording and play back, etc. • Communication infrastructure: Wireless and mobile networks make a crucial difference between mobile commerce and electronic commerce. This module may contain widearea networking stacks including TCP/IP and WAP, personal area networking stacks including infrared (IrDA), Bluetooth, and USB, abstract API for cellular standards, and GSM and CDMA circuit-switched voice and data and packet-based data. • Security: Security in mobile commerce is more vulnerable than in electronic commerce generally since mobile commerce communication is through wireless and mobile networks, which are more exposed to attacks. Mobile commerce security involves a wide variety of technologies, including authentication, cryptography, secure communications, secure mobile payment methods, etc. The 5th level also consists of three components: • Computer kernel: This is the central module of an operating system and it provides all the essential services required by the other parts of the operating system and applications. For example, it is responsible for resource allocation, low-level hardware interfaces, and process and task management, etc. • Power management: Battery life is short. This component manages the power consumption to prolong the battery life. • Real-time kernel: This component is not required for desktop PCs because they can usually take a few seconds, or even minutes, to react. Mobile handheld devices need real-time responses for some time-critical applications such as voice communication. The bottom level is the hardware controller. The hardware includes displays and memory. It is expected that hard disks will be added to the list in the near future.

Major Systems Although a wide range of mobile handheld devices are available in the market, the operating systems, the hub of the devices, are dominated by just three major organizations. The following two lists show the operating systems used in the top three brands of smart cellular phones and PDAs in descending order of market share: • Smart cellular phones: Microsoft Smartphone 2002, Palm OS 5, and Symbian OS 7. (VaughanNichols, 2003) • PDAs: Palm OS 5, Microsoft Pocket PC 2002, and Symbian OS 7. (PCTechGuide, 2003) The market share is changing frequently and claims concerning the share vary enormously. It is almost impossible to predict which will be the ultimate winner in the battle of mobile operating systems. The following four sub-sections briefly describe the above four systems in turn. Palm OS Palm OS (Palm Source, Inc., 2003) runs on almost two out of every three PDAs. Its popularity can be attributed to its many advantages, such as its long battery life, support for a


wide variety of wireless standards, and the abundant software available. The plain design of the Palm OS has resulted in a long battery life, approximately twice that of its rivals. It supports many important wireless standards, including Bluetooth and 802.11b local wireless and GSM, Mobitex, and CDMA wide-area wireless networks. The type of software often used on PCs is gradually becoming available for Palm OS such as spreadsheets, databases, document processors, messaging programs, and multimedia tools. To offset the increasing challenge from Pocket PC 2002, Palm introduced Palm OS 5, which runs an ARM processor, has a high-resolution (320×320) color screen, 16 MB of memory, and built in voice recorder, directional pad, built-in Bluetooth and media playback capability (MP3/OGG/WAV), and is complete with a speaker and headphone jack. Microsoft Smartphone The Smartphone (Microsoft Corp., 2003b) functions include: voice, SMS, and instant messaging services; email that can be received from sources such as the Outlook messaging and collaboration client, Exchange, IMAP, and POP3 services; and personal information management (PIM) applications such as calendar and contacts. The Smartphone 2002 platform is based on the Microsoft Windows CE 3.0 operating system, and contains many of the same core applications that are available on Pocket PC-based computing devices, including email, PIM tools, and Pocket Internet Explorer Web software. The primary Smartphone architecture consists of four layers: • Applications/UI: The top level refers to the Smartphone shell and customer-level applications such as Pocket Internet Explorer, the Inbox, the control panel, and the phone dialer. • Logic: This level contains system application logic that can be used by the application layer. Examples of this include the control of network connections and synchronization capabilities. • Core APIs: This level provides the interfaces between the low-level architecture components (Operating System, Smartphone software, and radio stack) and the application/logic layers. • Radio Stack: The bottom level refers, in general, to the architectural components responsible for voice and data control and data transmission. Microsoft Pocket PC In 1996, Microsoft launched Windows CE, a version of the Microsoft Windows operating system designed specially for a variety of embedded products, including mobile stations. However, it was not well received primarily because of battery-hungry hardware and limited functionality, possibly due to the way that Windows CE was adapted for mobile stations from other Microsoft 32-bit desktop operating systems. To compete with Palm OS, Microsoft later introduced Pocket PC (Microsoft Corp., 2003a), which was designed with better service for mobile users in mind and offers far more computing power than Windows CE. Moreover, the latest version introduces support for Bluetooth, IEEE 802.11b, and mobile phone technologies such as CDPD, CDMA, and GSM, and allows access to corporate information via a number of connectivity options, including VPN, WAN, LAN, and PANs.


Symbian OS EPOC16 from Psion Software is a 16-bit version of an operating system that has been available for several years and is embedded in many mobile stations; EPOC32 is a 32-bit open operating system that supports preemptive multitasking. In mid-1998, Psion joined forces with Ericsson, Nokia, and Motorola to form a new joint venture called Symbian OS (Dixon, 2003), with the aim of establishing EPOC as the de facto operating system for mobile stations. Unlike Windows CE, it was planned from the beginning to be a full operating system of mobile stations. It includes the following key features: integrated multimode mobile telephony, an open application environment, multi-tasking, multimedia, and data synchronization. MOBILE CENTRAL PROCESSING UNITS The core hardware in mobile handheld devices is the mobile processors, and the performance and functionality of the devices are largely dependent on the capabilities of the processors. There used to be several brands available, but recently mobile processors designed by ARM Ltd. have begun to dominate the market. Requirements of a Mobile CPU Handheld devices are becoming more sophisticated and efficient every day and mobile users are demanding more functionality from the devices. For example, in 2002 In-Stat/MDR predicted that worldwide mobile Internet access device unit shipments would increase from approximately 430 million that year to approximately 760 million in 2006 (In-Stat/MDR, 2002). To achieve this advanced functionality, in addition to the obvious feature, low cost, today’s mobile processors must have the following features: • High performance: The clock rate must be higher than the typical 30 MHz for Palm OS PDAs, 80 MHz for cellular phones, and 200 MHz for devices that run Microsoft’s Pocket PC. • Low power consumption: This prolongs battery life and prevents heat buildup in handheld devices that lack the space for fans or other cooling mechanisms. • Multimedia capability: Audio/image/video applications are recurring themes in mobile commerce. • Real-time capability: This feature is particularly important for time-critical applications such as voice communication. ARM Processors A few mobile processors such as Motorola Dragonball and Intel Pentium M were designed, manufactured, and sold by chip-making companies such as Motorola, Intel, and Texas Instruments. Now, however, the cores and architectures designed by Cambridge-based ARM Holdings Ltd. have begun to dominate the market. ARM is the industry's leading provider of 16/32-bit embedded RISC microprocessor solutions. The company does not actually produce chips, but instead licenses its RISC processors, peripherals, and system-chip designs to electronics companies. ARM's microprocessor cores specifically address the needs of advanced operating systems, real-time, and multimedia applications.


Figure 8 ARM11 microarchitecture, © 2003 ARM, Ltd. Reprinted with permission

Figure 8 shows the ARM11 pipeline structure. This is the first implementation of the ARMv6 instruction set architecture (ISA), and was developed specifically with the needs of next-generation consumer, wireless, networking, automotive products, and consumerentertainment applications in mind (Cormie, 2003). The ARM11 microarchitecture targets a 330-400 MHz worst case on 0.13µm foundry processes, delivering 400 to 500 Dhrystone MIPS. The ARM11 microarchitecture was designed to meet the low power requirement of batterypowered and high-density embedded applications, consuming less than 0.4mW/MHz on 0.13µm foundry processes. In addition to supporting 32-bit ARMv6 ISA, it has the following features: • Supporting Thumb 16-bit instruction set, • ARM DSP extensions, • SIMD (Single Instruction Multiple Data) media processing extensions deliver up to 2× performance for audio and video processing, • Better power/performance trade-off (0.4mW/MHz in 0.13µm), • An 8-stage integer pipeline improving performance, • Separate load-store and arithmetic pipelines, • A 64-bit memory system speeding data access, • Speedy interrupt response and real-time performance, and • Vector Floating Point coprocessor for automotive controls and 3D graphics acceleration.

MICROBROWSERS Microbrowsers are a miniaturized version of desktop browsers such as Netscape Navigatorsand Microsoft Internet Explorers. They provide graphical user interfaces that enable mobile users to interact with mobile commerce applications. Features Due to the limited resources of handheld devices, microbrowsers differ from traditional desktop browsers in the following ways:


• • •

smaller windows, smaller footprints, and fewer functions and multimedia features.

Several microbrowsers, such as Microsoft Mobile Explorer and Wapaka Java MicroBrowser, are already available. America Online, Inc., the parent company of the Netscape Network, and Nokia are developing and marketing a Netscape-branded version of Nokia's WAP microbrowser, with AOL enhanced features, for use across a wide variety of mobile handheld devices. Figure 9 shows a typical microbrowser, a Mobile Browser version 7.0 from Openwave Systems, which includes the following features: compatibility with WAP or i-mode, multimedia support, color images and animation, and dual network stack, HTTP and WSP, support (Openwave Systems Inc., 2003).

Figure 9 Openwave® Mobile Browser version 7 Technologies Several markup languages are used to present mobile contents on microbrowsers. These may not be able to handle all the languages currently used, therefore certain contents may not be displayed by some microbrowsers. Microbrowsers usually take the following four approaches, as shown in Figure 10, to display mobile contents (Lawton, 2001): 1. Wireless language direct access: A microbrowser supports some kinds of wireless languages, such as WML, CHTML, and XML, and directly displays the contents written in a wireless language supported by that microbrowser. 2. HTML direct access: This approach displays the HTML contents directly with, no intervention, but it may distort the contents. For example, large images can not be displayed on the small screens of microbrowsers. 3. HTML to wireless language conversion: Some mobile middleware provides conversion software to convert an HTML script to a script of the wireless language supported by that microbrowser. For example, i-mode includes a Corporate Conversion Server that converts existing HTML files into i-mode-compatible HTML, the CHTML.


4. Error: If the microbrowsers are not able to handle the contents, they simply display an error code such as “Invalid WML code.” Some microbrowsers, like most desktop browsers, can automatically send and receive information via cache, which is known as Web caching (Davison, 2001). Web caching has significant advantages such as reduced bandwidth consumption, server load, and latency. Together, the advantages make the Web less expensive and improve its performance. Microbrowser

Microbrowser

Microbrowser

Microbrowser

Wireless language Wireless language

HTM L

Converter

Error

HTM L

Wireless language

HTM L

HTM L

A language

Web servers

Figure 10 Four approaches for microbrowsers to display mobile contents

INPUT/OUTPUT DEVICES, MEMORY, BATTERIES, AND SYNCHRONIZATION The three components of mobile handheld devices, mobile OSs, mobile CPUs, and microbrowsers, result in a significant difference between handheld devices and desktop PCs. However, the remaining components do not play such a crucial role. This section briefly introduces the remaining components of handheld devices, which include: i) input/output devices, ii) memory, and iii) batteries, as well as synchronization with desktop PCs, notebooks, and other peripheral devices. Input/Output Devices Various I/O devices have been adopted by mobile handheld devices. The only major output device is the screen, whereas there are several popular input devices, including: • Keyboards: There are two kinds of keyboards: built-in keyboards and external, plug-in keyboards. The problem with the former is that they are too small for touch-typing, whereas the latter suffers from inconvenience. Fabric keyboards that can be rolled up or folded


around the handheld devices are being developed to relieve the problem of external keyboards. • Touch screens/writing areas with a stylus: A touch screen is a display that is sensitive to human touch, allowing a user to interact with the applications by touching pictures or words on the screen, and a stylus is an input device used to write text or draw lines on a surface as input to a handheld device. A handheld device equipped with a writing area and a stylus needs a handwriting recognition function, but existing systems do not yet have a satisfactory recognition rate. Graffiti, employed by many handheld devices, is the most popular writing software. Some mobile handheld devices can also react to voice input by using voice recognition technology.

Memory Desktop PCs or notebooks usually have between 64 to 256 Mbytes of memory available for users, whereas handheld devices typically have only 4 to 64 Mbytes. PDAs normally have more storage space than smart cellular phones. The former commonly have 16 Mbytes, and the latter may have a memory size as low as a few Kbytes. Three types of memory are usually employed by handheld devices: • Random access memory (RAM): There are two basic types of RAM, dynamic RAM (DRAM) and static RAM (SRAM). Dynamic RAM, the more common type, needs to be refreshed thousands of times per second in order to hold data, whereas static RAM does not need to be refreshed, making it faster but also more expensive than dynamic RAM. Both types of RAM are volatile; i.e., they do not retain their contents when the power is switched off. • Read-only memory (ROM): ROM is manufactured with fixed contents, and it is usually used to store the programs that boot the device and perform diagnostics. It is inherently nonvolatile storage, in contrast to RAM. • Flash memory: This is a kind of non-volatile storage similar to EEPROM (electrically erasable programmable read-only memory), but updating can only be done either in blocks or for the entire chip, making it easy to update. Flash memory is not as useful as random access memory because RAM can be addressable down the byte (rather than the block) level. It is expected that hard disks, which provide much more storage capacity, will be adopted by handheld devices in the near future. A comprehensive survey of storage options can be found in Scheible (2002). Batteries Rechargeable Lithium Ion batteries are the batteries most commonly used by handheld devices. The life of this kind of battery is short, generally only a few hours of operating time. Battery technology will not significantly improve unless and until manufacturers begin to switch to fuel cells, which is unlikely in the near future. A fuel cell operates like a battery, but unlike a battery, a fuel cell does not run down or require recharging and will continue to produce energy in the form of electricity and heat as long as fuel is supplied. Since the fuel cell relies on chemical energy rather than combustion, emissions would be much lower than emissions from the cleanest existing fuel combustion processes.


Synchronization Synchronization connects handheld devices to desktop computers, notebooks, and peripherals in order to transfer or synchronize data. The traditional method of synchronization uses serial cables to connect handheld devices and other computing equipment. Now, however, many handheld devices use either an infrared (IR) port or Bluetooth technology to send information to other devices without needing to use cables: • IrDA Data (Infared Data Association, 2003), a standard formulated by the Infrared Data Association to ensure the quality and interoperability of infrared hardware, is designed for data transfer over distances of up to one meter, acting as a point-to-point cable replacement. • Bluetooth wireless technology is a specification aiming at simplifying communications among handheld devices, printers, computers, and other devices based on short-range radio technology. The Bluetooth 1.1 specifications (Bluetooth SIG, Inc., 2003) consist of two documents: the Core, which provides design specifications, and the Profile, which provides interoperability guidelines. MOBILE COMMERCE APPLICATIONS The applications of electronic commerce are already widespread; mobile commerce applications not only cover these existing transactions but also include new ones. For example, some tasks that are not feasible for electronic commerce, such as mobile inventory tracking and dispatching, are possible for mobile commerce. This section will discuss these new applications and explore the new opportunities that are arisen from this new area. Categories of Mobile Commerce Applications Table 3 lists the major mobile commerce applications (Gordon & Gebauer, 2001; Sadeh, 2002), along with details of each. Mobile Category Commerce Education Enterprise resource planning Entertainment Health care Inventory tracking and dispatching

Table 3 Major mobile commerce applications Major Applications Clients Mobile transactions and payments Business Mobile classrooms and labs Schools and training centers Resource management Games/images/music/video downloads and online gaming Accessing and updating patient records Product tracking and dispatching

Traffic

Global positioning, directions, and traffic advisories

Travel and ticketing

Travel management

All Entertainment industry Hospitals and nursing homes Delivery services and transportation Transportation and auto industries Travel industry and ticket sales


Commerce Commerce is the exchange or buying and selling of commodities on a large scale involving transportation of goods from place to place. It is boosted by the convenience and ubiquity conveyed by mobile commerce technology. There are many examples showing how mobile commerce helps commerce. For example, consumers can buy products from a vending machine or pay a parking fee by using their cellular phones, and mobile users can check their bank accounts and perform account balance transfers without needing to go to a bank or access an ATM. Education Many schools and colleges are facing problems due to a shortage of computer lab space, separation of classrooms and labs, and the difficulty of remodeling old classrooms for wired networks. To relieve these problems, wireless LANs are often used to hook PCs or mobile handheld devices to the Internet and other systems. As a result, students are able to access many of the required resources without taking up valuable lab space. Enterprise Resource Planning (ERP) ERP is an industry term for the broad set of activities supported by the type of multi-module application software that assists a manufacturer or other organization manage important aspects of its business, including product planning, purchasing parts, maintaining inventories, interacting with suppliers, providing customer service, and tracking orders. The ERP issues that are particularly relevant to mobile commerce include tracking the location of goods and services, locating specific items, and transmitting warnings about aging components. Entertainment Entertainment has always played a crucial role in Internet applications and is probably the most popular application for the younger generation. Mobile commerce makes it possible to download game/image/music/video files at anytime and anywhere, and it also makes on-line games and gambling much easier to access and play. It is projected that by 2005, 80 percent of all mobile users in the United States and Western Europe will play mobile games at least occasionally (Leavitt, 2003). Health Care The cost of health care is high and mobile commerce can help to reduce it. By using the technology of mobile commerce, physicians and nurses can remotely access and update patient records immediately, a function which has often incurred a considerable delay in the past. This improves efficiency and productivity, reduces administrative overheads, and enhances overall service quality. Inventory Tracking and Dispatching Just-in-time delivery is critical for the success of today’s businesses. Mobile commerce allows a business to keep track of its mobile inventory and make time-definite deliveries, thus improving customer service, reducing inventory, and enhancing a company’s competitive edge. Major delivery services such as UPS and FedEx have already applied these technologies to their


business operations worldwide with great success.

Traffic Traffic is the movement of vehicles or pedestrians through an area or along a route. The passengers in the vehicles and the pedestrians are all mobile objects, ideal clients of mobile commerce. Also, traffic control is usually a major headache for many metropolitan areas. Using the technology of mobile commerce can easily improve the flow of traffic in many ways. For example, a mobile handheld device can have the capabilities of a GPS (Global Positioning System), such as determining the driver’s exact position, giving directions, and advising on the current status of traffic in the area. A traffic control center could also monitor and control the traffic according to the signals sent from mobile devices in the vehicles. Travel and Ticketing Travel expenses can be costly for a business. Mobile commerce could help reduce operational costs by providing mobile travel management services to business travelers. It can be used to provide assistance to customers by using the mobile channels to locate a desired hotel nearby, purchase tickets, make transportation arrangements, and so on. It also extends the reach of relationship-oriented companies beyond their current channels and helps the mobile users to identify, attract, serve, and retain valuable customers. SUMMARY The emerging wireless and mobile networks have extended electronic commerce to another research and application area: mobile commerce. Internet-enabled mobile handheld devices are one of the core components of mobile commerce systems, as they are needed for mobile users to directly interact with mobile commerce applications. Understanding the devices and knowing their functions and capabilities is vital for the success of mobile commerce applications. A handheld device relies on a wide range of disciplines and technologies for its success. To facilitate the understanding, this paper broke down the functions of a handheld device into six major components, which can be summarized as follows: 1. Mobile operating systems: Simply adapting desktop operating systems for handheld devices has proved to be futile. A mobile operating system needs a completely new architecture and different features to provide adequate services for handheld devices. A generalized mobile operating system structure can be visualized as a six-layer stack: i) applications, ii) GUI, iii) API framework, iv) multimedia, communication infrastructure, and security, v) computer kernel, power management, and real-time kernel, and vi) hardware controller. 2. Mobile central processing units: Handheld devices are becoming more sophisticated and efficient every day and mobile users are demanding more functionality from their devices. To achieve this advanced functionality, in addition to the obvious feature, low cost, today’s mobile processors must have the following features: i) high performance, ii) low power consumption, iii) multimedia capability, and iv) real-time capability. The cores and architectures designed by Cambridge-based ARM Holdings Ltd. have begun to dominate the mobile CPU market. 3. Microbrowsers: Microbrowsers are miniaturized versions of desktop browsers such as Netscape Navigator and Microsoft Internet Explorer. They provide graphical user interfaces


that allow mobile users to interact with mobile commerce applications. Microbrowsers usually use one of the following four approaches to return results to the mobile user: i) wireless language direct access, ii) HTML direct access, iii) HTML to wireless language conversion, and iv) error. 4. Input/output devices: Various I/O devices have been adopted by mobile handheld devices. The only major output device is the screen, but there are several popular input devices, among them: i) keyboards and ii) touch screens/writing areas that need a stylus. 5. Memory: Three types of memory are usually employed by handheld devices: i) RAM, ii) ROM, and iii) flash memory. Hard disks, which provide much more storage capacity, are likely to be adopted by handheld devices in the near future. 6. Batteries: At present, rechargeable Lithium Ion batteries are the most common batteries used by handheld devices. However, the life of this kind of battery is short and the technology will not significantly improve unless and until manufacturers begin to switch to fuel cells, which may not happen for at least several years. Synchronization connects handheld devices to desktop computers, notebooks, or peripherals to transfer or synchronize data. Without needing serial cables, many handheld devices now use either an infrared (IR) port or Bluetooth technology to send information to other devices. The applications of electronic commerce are already widespread and new mobile commerce applications are also becoming possible.

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Technological Innovativeness and Organizational Culture in Hong Kong

Gary Y. F. Wong City University of Hong Kong E-Mail: [email protected] Richard Y. K. Fung City University of Hong Kong E-Mail: [email protected] ABSTRACTS This paper attempts to explore the relationship between technological innovativeness and organizational culture in Hong Kong. It measures both technical and administrative innovations status of organizations. A questionnaire survey is conducted to collect information from various industries in Hong Kong. Also included is the temporal information of innovations. The research uses path analysis to measure the impacts of three organizational factors on innovativeness. Organizational characteristics, organizational climate and organizational context are the factors that used in the research. As shown in the research, learning ability, centralization, specialization, external orientation, formalization, sufficient slack, achievement orientation and risk orientation are influencing the innovativeness in various perspectives. Keywords: Organizational culture; Technological innovation; Organizational learning; Hong Kong INTRODUCTION In today’s business world, organizations are strengthening their competitive advantage in their marketplaces. They are improving their organization’s efficiency and shortening their response time to markets. In order to achieve their goals, organizations must strengthen their internal processes to make themselves ready to react to market needs, as well as to competitors. Nowadays, most organizations recognized that business process reengineering is a useful tool to maintain their competitive advantage. However, business process reengineering is a huge project for an organization. Possibly, the project will span across the entire organization and affect every aspect of operations. Besides, business process reengineering is also a risky process, as many cases ended up in failure because the changes were not handled well. To this end, most organizations employ management tools, which are available from markets to support the business process reengineering. Information technology solutions are


widely used in different industries for business process reengineering. It is widely accepted that information technology innovations are providing guidance to organizations on effective business process reengineering. Innovation is commonly viewed as creativity – creating new ideas and knowledge. However, new ideas will not contribute to businesses until people un-shelf the new ideas from the laboratory, implement them, and generate values to customers. Kaner (1990) states, “A good new idea means little-except risk-without….excellence in execution.” That means if an organization has a lot of new idea, the organization is creative. If the organization can turn its idea to generate values, the organization is innovative. The Society of Management Accountants describes “innovation…fundamental to the quest for profitable, sustainable growth.” A research done on the rate of return for 17 successful innovations shows a mean return of 56% compared with an average ROI of 16% (Horibe, 2001). In today’s business world, organizations have recognized that innovation is the most important criterion for success in the future. Technological innovations are playing a major role in today’s IT world, from desktop applications, such as Windows, Microsoft Offices, etc to sophisticated enterprise solutions. Information technologies provide effective tools or best practices to business processes. Especially on business process enhancements, information technology solutions automate and integrate the majority of an organization’s business processes. They enable data sharing and standardized practices across the entire organization. Aladwani (2001) states that IT systems help the different parts of the organization share data and knowledge. Information technologies enable an organization to produce and access information on a real-time basis. For those On Line Transactions Processes systems (OLTP), such as Enterprise Resources Planning (ERP), they provide a backbone for the further extension of functionality through bolt on and other solutions, for example, business intelligent systems (BI) for marketing analysis. Costs reductions and improvement on management of business processes are the other “gains” from IT systems. PREVIOUS RESEARCH The Influence of Organizational Culture to Technological Innovation Different aspects of organizational culture were reviewed to explore the interrelationship between organizational culture and technological innovation in the past. The reviews focused on organizational culture’s influence on an organization’s technological innovations (Claver et al., 1998; Martins and Terblanche, 2003). In referring to the research carried out by Claver et al. (1998), the research suggests that technological innovations were the intersection of several factors. They were Innovation Culture, CEO’s Acceptance and Technology Culture. On the other hand, Martins and Terblanche (2003) suggest that the determinants of organizational culture that influence creativity and innovation included Strategy, Structure, Support Mechanisms, and Behaviour that encourages innovation and Communication. The Impact of Information Technology on Organizational Structures The research performed by Burn (1989) focused on the impact of information technology on organizational structures, which was a project in the Department of Computing Studies of Hong Kong Polytechnic. The project aimed to 1) Identify whether any correlation exists between the Structure of an organization and its usage of Information Technology; 2) Measure the


effectiveness of usage and identify whether a direct relationship exists between specific approaches adopted by organizations, the organization structure and the benefits; and 3) Develop a framework for organizations on strategic planning in the development and use of information systems/technology. Burn (1989) based on Michael Earl’s theories, which identified three types of framework for the analysis of IT and IS strategies. They are 1) Awareness: Helps to identify where strategic opportunities exist, 2) Opportunity: Provides more detailed techniques or models for analysis or identification of strategic uses of Information Technology and 3) Positioning: Helps to assess the strategic importance of Information Technology and how the information system functions can be managed. Earl also suggests that with a workable set of all three frameworks, it is able to create a three-level complementary set of frameworks for an analysis that: 1) Shows what is possible; 2) Helps identify applications; 3) Guides how to get there. The concepts are shown in Table I. Table 1 Three-level complementary frameworks (Source: Burn, 1989) Quality Purpose Scope Use

Awareness Vision Possibility Education

Frameworks Opportunities Ends Probability Analysis

Positioning Means Capability Implementation

Instead of providing detailed models to all three levels (Awareness, Opportunities and Positioning), Burn (1989) provided an integrated approach to integrate all three levels at a Meta level and set the groundwork by doing a micro-level analysis of Awareness models. Furthermore, at the Awareness level, Burn (1989) concentrated on evaluating the usage of information technology in Hong Kong and identifying specific organizational configurations where proven opportunities exist to exploit information technology. Detailed case studies were done to assess the potential impact of information technology and hence to provide a general awareness of what was happening. The Awareness model in which Burn (1989) provided was examples by analogy rather than direct guidance for usage. According to Burn (1989), businesses in Hong Kong comprise mainly small and medium enterprises that account for around 75% of the total. These small organizations commonly show little segregation of management from ownership or formal organizational structures. Besides, many listed companies are family controlled. They grow by acquiring subsidiaries and the style of management is still very much owner centred with family members dominating the core management. CATEGORY OF INNOVATION ADOPTION RESEARCH Innovation adoption research can be divided into two major categories. One category of research focuses on the relationship between government policy, social status and economic situation, and innovativeness of organizations. This category is defined as “external influence research” in this research. Another category of research concerns with exploring the interrelationship between organizational culture and technological innovation. This category is


defined as “internal influence research” in this research. External Influence Research Research studies in this stream concentrate on the influences from social status, economic and historical profiles, and the policies to promote economic and technological progress. The focus is on the identification of influence from external environment to the innovativeness of organizations. Internal Influence Research Research studies in this stream concentrate on the internal factors that contribute to the innovativeness of organizations, such as organizational climate, organizational characteristics, learning abilities, number of innovation adoptions, and the consistency of adoptions. The innovativeness of an organization is determining by the number of innovation adoptions and consistency of adoptions in comparing with other organizations. The internal influence research forms the framework of this research. One of the areas of this research is identifying the organizational determinants of innovation adoptions, especially of organizations in Hong Kong. Cultural factors that are affecting innovativeness may vary from country to country. This research uses results from other researcher as reference and examines determinants that appear to contribute to the adoption of innovations, they are including the climate of organizations, the characteristics of organizations and the context of organizations. The other area of this research is to identify the correlation between these organizational determinants of innovation adoptions and administrative, technical innovativeness. MODEL DEVELOPMENT In considering past research on organizational culture and innovativeness (Nystrom et al., 2002; Subramanian and Nilakanta, 1996), Nystrom et al. (2002) points out that organizational slack is a key factor that affecting the adoptions of innovations. Slack is a resource that enables an organization to handle demands raised internally and externally (Ahmed, 1998). Judge et al. (1997) states sufficient and continue available resource would have positive impact to innovation. Only those new projects that have sufficient funding and staffing resources, and management commitment have chance to succeed (Christensen, 2000). Nystrom et al. (2002) also suggests that organizational climate, in terms of risk orientation, external orientation, and achievement orientation also influence the innovativeness of organizations. Lewin and Douglas Mcgregor define the term climate by social climate and organizational climate, which is reflected by the practices, procedure and rewards systems of an organization. Climate is closely allied with culture in which climate is the practices of peoples operate an organization and create procedures and policies for an organization. Culture, on the other hand, is reflects beliefs and values of an organization (Ahmed, 1998). Besides, organizational characteristics, in terms of formalization, centralization and specialization moderate the relationship between characteristics and innovativeness (Subramanian and Nilakanta, 1996). Three aspects measure the innovativeness of organizations. Nystrom et al. (2002) measured it in terms of the degrees of radical of adopted innovations, relative advantage of adopted innovations and number of adopted innovations. On the other hand, Subramanian and Nilakanta


(1996) measured innovativeness in terms of number of innovation adoptions, time of innovation adoptions and consistency of innovation adoptions. It is found that except the measurement of number of adopted innovations, the other measurements are different. Considerable research exists on the organizational culture and innovativeness, like the research of Nystrom et al. (2002), the temporal dimension of innovativeness was not examined. Therefore, this research adopts the measurements used by Subramanian and Nilakanta (1996) in order to capture the temporal dimension. As Subramanian and Nilakanta (1996) suggest, “truly innovative organizations are those that exhibit innovative behaviour consistently over time”. Research activities of Nystrom et al. (2002) and Subramanian et al. (1996) were done in USA for the banking and the medical industries. As mentioned earlier in this paper, organizational culture that is affecting innovativeness may vary from country to country. Therefore, this research intends to examine the culture of organizations in Hong Kong using the research model shown in Figure 1.

Moderator Variables Organizational Climate 1. Risk Orientation 2. External Orientation 3. Achievement Orientation Organizational Characteristics 1. Formalization 2. Centralization 3. Specialization

Outcome Variables Organization Innovativeness 1. No. of Innovation Adoptions 2. Time of Innovation Adoptions 3. Consistency of Innovation Adoptions

Influence Variables Organization Context 1. Learning Abilities 2. Organization Slack Figure 1 Research Model

RESEARCH METHODOLOGY This research adopted the “dual core” typology of innovations. Subramanian and Nilakanta (1996) also adopted this typology in their previous research named as technical innovations and administrative innovations. A list of the innovations was compiled using a literature search and an empirical search. The list covered systems and mechanisms that are popular to organizations. The final list contained 7 technical innovations and 17 administrative innovations elements and a questionnaire was used to collect data. Administrative Innovations and Technical Innovations This research differentiated the technical innovations and administrative innovations according to the criteria suggested by Damanpour et al. (1989).


“Administrative innovations are defined as those that occur in the administrative component and affect the social system of an organization. The social system of an organization consists of the organizational members and the relationships among them. It includes those rules, roles, procedures, and structures that are related to the communication and exchange between organizational members. Administrative innovations constitute the introduction of a new management system, administrative process, or staff development program. An administrative innovation does not provide a new product or a new service, but it indirectly influences the introduction of new products or services or the process of producing them. Technical innovations are defined as those that occur in the operating component and affect the technical system of an organization. The technical system consists of the equipment and methods of operations used to transform raw materials or information into products or services. A technical innovation, therefore, can be the adoption of a new idea pertaining to a new product or services, or the introduction of new elements in an organization’s production process or service operations.” Evan (1966) suggests administrative and technical innovations are reflecting the difference between social structure and technology. According to Damanpour (1984) and Daft (1982), technical innovations are processes and technologies that directly related to the production of products or provide services directly related to the business activity an organization. While administrative innovations are related to back office administrations, such as human resources management, administrative management, which are indirect to the production of products and services (Damanpour, 1984; Kimberly, 1981). However, there is no standard on the definition of innovation dimensions (Gopalakrishnan and Damanpour, 1997). Therefore, this research defined innovation dimensions by the criteria suggested by Daft (1982), Damanpour, (1984, 1989), Evan (1966), Gopalakrishnan and Damanpour (1997) and Kimberly (1981). TEMPORAL DIMENSIONS MEASUREMENT This research also adopted the idea of Subramanian and Nilakanta (1996) to measure the temporal dimensions of innovativeness. The questionnaire was used to collect time dimension information of organizations when they adopted an innovation item. Three temporal dimensions of innovativeness were measured on both administrative innovations and technical innovations. Mean Number of Innovation Adoptions (MNIA) The mean number of innovation adoptions of an organization was calculated by the following formula. Total number of innovations adopted MNIA = No. of years between last innovation and first innovation The number of years between the adoption of the first and the last innovation in an organization was firstly calculated. Secondly, the total number of innovations that an organization adopted over the period was determined. Finally, the mean number of an organization on innovation adoptions was computed by dividing the total number of innovation adoptions by number of years taken.


Mean Time of Innovation Adoptions (MTIA) The mean time of innovation adoptions of an organization was calculated by using the following formula. As suggested by Subramanian and Nilakanta (1996), use the mean time of innovation adoptions to measure the time of innovation adoption of each organization relative to the other organizations. MTIA = (Last year of adoption of an innovation among organizations + 1) – The year of adoption of an innovation in an organization This formula was applied to each innovation of organizations to calculate the mean time of adoptions. Firstly, the last year of adoption of an innovation among organizations was determined and one was added to the year. Secondly, the year of an organization adopted the innovation was subtracted by the value. For example, in the case of computerized customer billing system innovation, if organization “ABC” adopted the system in 1985, and if the last adopter of the system was on 2002, therefore, the MTIA of computerized customer billing system innovation of “ABC” is calculated by 2003 (i.e. 2002 + 1) – 1985 and the score is 18. However, if another organization adopted the system on 1999, the MTIA would be calculated by 2003 (2002 + 1) – 1999 and the score is four. Hence, organizations that adopted an innovation earlier among the others would have a higher score. The last adopter would have a score of one. For those organizations that did not adopt the innovation would have a zero score. The mean time of innovation adoption of an organization was calculated by using the score of each innovation. Consistency of the Time of Adoptions (CTA) As suggested by Subramanian and Nilakanta (1996), this variable was used to measure the consistency of organizations that adopted innovations early or late. It was computed by dividing the standard deviation of a set of scores by the mean value of that set of scores. Hence, organizations that adopted innovations consistently earlier or later than others would have lower coefficients of variability. The CTA itself did not measure the early or late innovation adoption of organizations. ORGANIZATIONAL CHARACTERISTICS Montes et al. (2003) defines the structural characteristics of innovations. The structural characteristics defined as environment, size, complexity, differentiation, formalization, centralization and strategy. This research covered three organizational characteristics. They measured the extent of formalization, the extent of centralization and the extent of specialization of organizations. Each category consisted of several questions in the questionnaire. The mean value of each extent was calculated for each organization. In the other words, each organization had three scores for the organizational characteristics measurement. ORGANIZATIONAL CLIMATE From the research of DeDreu et al. (1999), two dimensions of climate influence the innovation process of organizations. They are communication and freedom to express opinions. This research examined three types of organizational climates. They measured the extent of risk


orientation, the extent of external orientation and the extent of achievement orientation. Similar to the organizational characteristics, each category consisted of several questions in the questionnaire. The mean value of each extent was calculated for each organization. ORGANIZATIONAL CONTEXT The organizational context consists of organizational slack and learning abilities. Considerable research exists on innovativeness points out that learning abilities are the key factor of organizations (Ansoff, 1988; Colin, 2000; Grusky, 1970; Judson, 1966; Kaufman, 1971; Kotter et al., 1986; Lawrence, 1954; McNurry, 1973; Nystrom et al., 2002; Sayles, 1960; Waddell et al., 1998). Besides, organizational slacks also a key contributor to innovativeness of an organization (Nystrom et al. 2002; Subramanian et al., 1996). This research covered these contexts in the questionnaire and measured by mean scores. Table 2 gives a description of the dimensions of climate, slack, characteristics and learning abilities used in this research. The dimensions were measured by using a five-item scale. The questionnaire used measurements from Subramanian et al. (1996), Nystrom et al. (2002) and Dixon (1994) as guidelines and were modified to suit the requirement of this research. The Appendix A reproduces the questionnaire used in this research. Table 2 Dimensions of climate, slack, characteristics and learning abilities Dimensions Organizational climate

Concepts This dimension examines three well-known dimensions: risk orientation, external orientation, achievement orientation and organizational slack. Organizational characteristics This dimension examines some structural characteristics of an organization, such as formalization, centralization and specialization. Learning abilities This dimension examines the abilities of an organization to maintain as a learning organization and sustains the competitive edge. Innovativeness This dimension examines an organization’s adoption of technical and administrative innovations. It also collects temporal information of innovation adoptions. Note: Modified from Subramanian et al. (1996), Nystrom et al. (2002) and Dixon (1994)

CASE STUDY Data collection Data collection was carried out during the period from January to March 2004, using a questionnaire survey. The realm of the sample was organizations in Hong Kong from various industries. Approximately, 266 organizations participated in the survey. Questionnaires were distributed by means of email systems and personally. The respondents were primarily senior


managers and engineers, from fourteen industries, mainly in the manufacturing, finance, transportations and construction industries. 74 responses were received. However, there were missing and invalid data in some questionnaires. These questionnaires were excluded from the data analysis. Therefore, the final sample embraced 70 questionnaires. The technical details of the survey are shown in Table 3.

Universe Geographical area Type of interview Sample size Confidence level Sampling error Scaling Sample design Minimum sample size

Table 3 Technical details of the survey Entities Hong Kong SAR, China Emailed structured questionnaire N = 70 95 percent +/- 0.2 scale points From 1 to 5 Random selection of sampling units N = 66

Validity and Reliability Table 4 shows the reliabilities of items used to measure the about mentioned factors. All items show acceptable levels of reliability. Table 4 Reliabilities of organizational measures Elements Organizational Climate External Orientation Achievement Orientation Organizational Slack Organizational Characteristics Formalization Centralization Specialization Learning Abilities

No. of Items

Inter-item Correlation (Cronbach's Alpha)

9 2 4

0.843 0.620 0.651

2 2 2 10

0.868 0.745 0.673 0.916

Path Analysis Path analyses were performed on the data collected by questionnaire survey. Two separate path analyses were carried out for the two types of innovations. Figure 2 and Figure 3 show the results of the analysis of administrative innovations and technical innovations respectively. Table 5 and Table 6 depict the correlations among all the relevant variables.


0.317

Risk Orientated

0.215

Formalization Mean of Administrative Innovation Adoption

0.307 0.215

Learning Abilities

External Orientated

0.513

Centralization

0.407

-0.305 Mean Time of Administrative Innovation Adoption

0.385 0.367

0.488

0.313-0.243 Achievement Orientated

Specialization

Consistency of Administrative Innovation Adoption

0.214

0.436 Organization Slack

Figure 2 Path analysis of administrative innovations

Table 5 Correlation matrix of administrative innovations Mean

Time

Consi st

Risk

Exter

Achie

Slack

Form

Cent

Spec

Mean

1

Time

-.279*

1

Consist

-.657**

.616**

1

Risk

.092

.012

.060

1

Exter

.192

.385**

.138

.383**

1

Achie

.313**

.040

-.165

.128

.491**

1

Slack

.019

.118

.114

.368**

.339**

.239*

1

Form

.075

.166

-.041

.197

.307**

.407**

.367**

1

Cent

.215*

-.305**

-.243*

.196

.028

.068

.056

.031

1

Spec

-.088

-.035

.214*

-.010

-.100

-.135

.090

-.067

-.183

1

Learn

.317**

.092

-.195

.215*

.513**

.488**

.436**

.524**

.084

.007

Learn

1


Mean = Mean number of administrative innovations Time = Mean time of administrative innovations Consist = Consistency of administrative innovations Risk = Risk orientation Exter = External orientation Achie = Achievement orientation Slack = Organizational slack Form = Formalization Cent = Centralization Spec = Specialization Learn = Learning abilities Table 6 Correlation matrix of technical innovations Mean

Time

Consist

Risk

Exter

Achi

Slack

Form

Cent

Spec

Mean

1

Time

-.345**

1

Consist

-.669**

.494**

1

Risk

.229*

-.043

-.088

1

Exter

.185

.192

.223

.383**

1

Achi

-.022

.117

.056

.128

.491**

1

Slack

.150

-.028

-.056

.368**

.339**

.239*

1

Form

-.014

.246*

.096

.197

.307**

.407**

.367**

1

Cent

-.166

-.201

-.122

.196

.028

.068

.056

.031

1

Spec

-.193

-.030

.388**

-.010

-.100

-.135

.090

-.067

-.183

1

Learn

.073

.169

.156

.215*

.513**

.488**

.436**

.524**

.084

.007

Mean = Mean number of technical innovations Time = Mean time of technical innovations Consist = Consistency of technical innovations Risk = Risk orientation Exter = External orientation Achie = Achievement orientation Slack = Organizational slack Form = Formalization Cent = Centralization Spec = Specialization Learn = Learning abilities

Learn

1


0.229 0.307

Risk Orientated

0.215

Mean of Technical Innovation Adoption

Formalization

Learning Abilities

0.513

External Orientated

0.407

0.246 Mean Time of Technical Innovation Adoption

Centralization

0.488

0.367 Achievement Orientated

Specialization

0.388

Consistency of Technical Innovation Adoption

0.436

Organization Slack

Figure 3 Path analysis of technical innovations

Administrative Innovation For administrative innovation, learning ability, centralization, specialization, and external orientation significantly associate with administrative innovativeness. High levels of learning ability associate with larger number of administrative innovation adoptions. High levels of learning ability also associate with the levels of risk orientation and the early adoption of administrative innovations. The research also indicates that high levels of centralization associate with larger number of administrative innovation adoptions. However, the high levels of centralization do not support the consistency adoptions and the early adoption of administrative innovations. Furthermore, high levels of specialization in an organization associate with the consistency of administrative innovations and high levels of external orientation associated with early adoptions. Table 7 shows the total causal effect analysis of administrative innovations.


Table 7 Total of causal effect analysis of administrative innovations Exogenous Variable

Endogenous Variable

Total Causal Effect

Learning Ability

Number of Administrative Innovation

0.47

Learning Ability

Risk Orientation

0.215

Learning Ability

Time of Administrative Innovation

0.198

Centralization

Number of Administrative Innovation

0.215

Centralization


-0.305

Centralization

Consistency of Administrative Innovation

-0.243

Specialization

Consistency of Administrative Innovation

0.214

External Orientation


0.385

Technical Innovation For technical innovation, learning ability, formalization, specialization and risk orientation significantly associate with technical innovativeness. High levels of learning ability associate with larger number of technical innovation adoptions. Formalization associate with early technical adoptions. Furthermore, high levels of specialization associate with consistency of technical innovation and the high levels of risk orientation lead to a larger number of technical innovations. External orientation, sufficient slack and achievement orientation contribute to early adoption of technical innovations. However, centralization does not have contribution to technical innovations. Table 8 shows the total causal effect analysis of technical innovations. Table 8 Total of causal effect analysis of technical innovations Exogenous Variable Endogenous Variable Total Causal Effect Learning Ability

Number of Technical Innovation

0.049

Formalization

Time of Technical Innovation

0.246

Specialization

Consistency of Technical Innovation

0.388

External Orientation


0.076

Organizational Slack


0.09

Achievement Orientation


0.1

Risk Orientation

Number of Technical Innovation

0.229

Common Factors of Administrative Innovation and Technical Innovation Addition to the specific factors that support the administrative innovations and technical innovations, these cores also share some factors. The factors are not depicted in the about sections and are listed in Table 9 separately in the interest of clarity. The result illustrates, learning ability, external orientation, achievement orientation and organizational slack significantly associated with formalization.


Table 9 Total of causal effect analysis of common factors Exogenous Variable Endogenous Variable Total Causal Effect Learning Ability Formalization 0.516 External Orientation Formalization 0.307 Achievement Orientation Formalization 0.407 Organizational Slack Formalization 0.367

SUMMARY In summary, the survey results illustrate that organizational climate and organizational characteristics do not have an indistinguishable relationship with dimensions of innovativeness. Besides, organizational factors have different effects on the adoption of administrative innovations and technical innovations. High degrees of learning ability and specialization affect the three dimensions of administrative innovations. Centralization affects the number of administrative innovations. However, it does not positively contribute to the consistency and early of administrative innovations. External orientation has direct effects on the early adoption of administrative innovations. In technical innovations, learning ability and risk orientation positively affect the number of innovation adoptions. Formalization affects the early adoptions positively while specialization significantly influences the consistency of technical innovations. The dimensions of external orientation, sufficient slack and achievement orientation influence the early adoption of technical innovations. However, centralization does not have contribution to technical innovations. Learning ability, external orientation, achievement orientation and organizational slack positively affect the formalization of organizations in both administrative and technical innovations. DISCUSSION The result of this questionnaire survey demonstrates various relationships between administrative innovativeness, technical innovativeness and organizational culture. The result of causal effect analysis of administrative innovations suggests the learning ability of an organization influences the number of administrative innovation adopted, the early adoption of administrative innovation. It seems to support a past research (Passfield, 2002) that learning ability is a major factor of an organization to innovate. The result also suggests that an organization has higher learning ability is comparatively risk orientated. It may due to a learning organization has a strong reviewing skills and high tolerance of ambiguity and able to take risk during an innovation process (Chaharbaghi and Newman, 1996). Besides, the result suggests an organization with a centralization characteristic is benefit from the large number of administrative innovation adoptions. It may due to the reason that it is more efficient for an organization to implement policies and procedures using a top down approach. That is, the top management team decide policies and procedures, which can suit the needs of an organization’s operation and escalate down to employees in the down stream. However, the centralization characteristic is not necessarily influences the early and consistency of administrative innovation adoptions. It seems that when a small group of people in an organization acts the decisionmaking role, usually the top management team, policies and procedures implementations are became inconsistent. It could be the result of the management team needs to handle a variety of


operational issues of an organization and the efforts that the team can devote to the administrative innovation are limited. Therefore, the top management team may implement new policies and procedures when there is an urgent need to the operation. It also explains why centralization characteristic influences the number of administrative innovation adoption. On the other hand, specialization characteristic result in consistency of administrative innovation. It is likely that, in contrast to the centralization characteristic, which does not promote the consistency of administrative innovation adoption, a group of people that dedicate to the development and implementation of policies and procedures can make the adoption more consistent. For example, some manufacturing organizations have a team of people focus on process reengineering. They review processes on shop floors and develop new working procedures to improve efficiencies and qualities. As discussed earlier, administrative innovation and technical innovation are associated with each other. A successful administrative innovation would require a certain degrees of technical innovation, and vice versa. In addition to the administrative innovation, the questionnaire survey result also demonstrates the causal effect analysis of technical innovations. The result suggests the early adoption of technical innovation is statistically associated with the formalization, external and achievement orientation characteristics and sufficient slack of an organization. The result seems to support the arguments of past researches that organization slack is essential to technical innovation. It may be due to the fact technical innovations projects are require sufficient financial support and expertise of perspective areas in order to carry out implementations and to resolve technical problems. The formalization of an organization can define the role of an individual in an organization by describing the job duty clearly using written job description. Therefore, employees in an organization can understand their role and perform the duties that are defined by the organization. It could help employees to concentrate on their work. The external and achievement orientation characteristics can help an organization to understand customer needs as well as the strategies of its competitors. Therefore, the organization can make a timely change on its strategies and it may involve the deployment of technological systems that help the organization to maintain its market place. It may explain an organization that is external and achievement orientations adopt technical innovation earlier than other organizations. The survey result also suggests the learning ability and the risk orientation of an organization influence the total number of technical innovation adoption. There appear to be a strong probability that an organization, which has higher ability to learn and able to tolerate failures and manage uncertainly will result in larger number of technical innovation adoption. The similar reason can be extended from the administrative innovation. It may due to a learning organization has a strong reviewing skills and high tolerance of ambiguity and able to take risk during an innovation process (Chaharbaghi and Newman, 1996). High degrees of specialization lead to consistency of technical innovation adoptions. The result indicates that employees should fully match the requirement of their functional areas and they should not often transfer from a department to another department. It may be the fact that when an employee is working in a functional area for a considerable period, the employee can have a good understand on the area and able to identify opportunities for improvement frequently. The survey also indicates another interesting result. A few organizational factors are influencing the administrative innovations of an organization, they are learning ability, centralization, specialization and external orientation. However, in technical innovations,


comparatively more organizational factors are influencing the innovativeness of an organization. They are learning ability, formalization, specialization, external orientation, organization slack, achievement orientation and risk orientation. It indicates an organization, which can succeed in the process of technical innovation need to manage different aspects of organizational culture. Some past researches also indicate that organization readiness plays a major role of innovations. Organization readiness is referring to the internal and external environment; vision, mission and values; knowledge management; management style; organization structure; individual, team and organizational learning; and organization memory. CONCLUSION Focus of Past Researches Considerable amount of research has done in the past on innovation and organizational culture by researchers. It covered a range of areas to examine the innovativeness of a specific country, industry, region, etc. As mentioned earlier, past research activities examined the relationships between the beliefs of top management team, culture of an organization and innovativeness. The researches define organizational culture into innovative culture, technology culture and culture based technological innovation. The researches are focusing on the internal factors that interrelated to the organizational culture in innovation. Another group of researchers consider the vision and mission are strategically influencing the innovativeness of an organization. Employees and employers should have common objectives and means to achieve objectives. Leadership and interpersonal relationships, as well as external environment, such as customer focus strategies are the factors that influence the innovativeness of an organization. Past researches also studied policies of governments and organizational structures that are promoting innovation. They compared the innovation progress status from the perspective of social status, economic, historical profiles and policies (Martinsons, 1998). These kinds of research studies provided conceptual models on managing the organizational culture in innovation, but did not attempt to measure the relationships between organizational culture and innovativeness of a specify country, region or industry. This research suggests classifying the about discussed past researches into two major categories. One category is “external influence research” while the other is “internal influence research”. This research employed the internal influence research as a framework and empirically measured the relationships between organizational culture and innovativeness of organizations of various industries in Hong Kong. Temporal Dimension Measurements Although many past researches have measured innovativeness and organizational culture, a standard methodology that researchers commonly use is not available. Some researchers measured it in terms of the degrees of radical of adopted innovations, the advantage of adopted innovations and the number of adoption. Other researchers included the temporal dimensions in their measurement. Theoretically, the degree of innovativeness of an organization could be different when it is measured by different methodologies. However, innovation is a continuously process that allies with the growth of an organization, the external and internal factors, such as the change of top management team, the vision and mission of an organization, the change of economic environment and the capability of employees. Therefore, this research measured the temporal dimensions of innovativeness that are introduced by Subramanian and Nilakanta


(1996). Administrative and Technical Innovation Measurements Some past researches suggest separate the administration innovation and the technical innovation and just measured one of the two aspects in their studies. This research measured both aspects using different set of questions in the questionnaire survey. It is likely that administrative innovations are associated with technical innovations, although characteristics that lead to these innovations are different. Organizational Factors that Affecting Innovativeness The results of this research identified learning ability, centralization, specialization, external orientation, formalization; sufficient slack, achievement orientation and risk orientation are influencing the innovativeness in various perspectives. It is to be hoped that this research has contributed by providing an insight to mangers in managing their organizations in innovation processes. Additional research is recommended to aggregate the findings together and develop a model to manage organizational culture in technological innovation. REFERENCES Ahmed, Pervaiz K. (1998), “Culture and Climate for Innovation”, European Journal of Innovation Management, MCB University Press, Vol. 1, No. 1, pp. 30-43. Aladwani, Adel M. (2001), “Change Management Strategies for Successful ERP Implementation”, Business Process Management Journal Vol. 7 No. 3, pp. 266-275 Ansoff, I., (1988), “The New Corporate Strategy”, John Wiley & Sons, New York, NY. Burn, Janice M. (1989), “The Impact of Information Technology on Organizational Structures”, Hong Kong Polytechnic, Hung Hom, Kowloon, Hong Kong. Chaharbaghi, Kazem and Newman, Victor (1996), “Innovating Towards an Integrated Learning Model”, Management Decision, Vol. 34, No. 4, pp. 5 – 13. Christensen,Clayton M. (2000), “The Innovator’s Dilemma”, Harper Business Essentials, pp. 119, 187. Claver, Enroque, Llopis, Juan, Garcia, Daniel and Molina, Hipolito (1998), “Organizational Culture for Innovation and New Technological Behaviour”, The Journal of High Technology Management Research, Vol. 9, No. 1, pp. 55-58. Colin Coulson-Thomas (2000), “Developing a corporate learning strategy”, Industrial and Commercial Training, Vol. 2, No. 3, pp. 84±88, MCB University Press. Daft, R. L. (1982), “A Dual-core Model of Organizational Innovation”, Academy of Management Journal, Vol. 21, pp. 193-210, In: Gopalakrishnan S. and Damanpour F. (1997), “A Review of Innovation Research in Economics, Sociology and Technology Management”, Omega International Journal of Management Science, Vol. 25, No. 1, pp. 15-28. Damanpour, F., Szabat, K. A. and Evan, W. M. (1989), “The Relationship between Types of Innovation and Organizational Performance”, Journal of Management Studies, Vol. 26, pp. 587 – 601. Damanpour, F. and Evan, W. M. (1984), “Organizational Innovation and Performance: The Problem of Organizational lag.”, Administrative Science Quarterly, Vol. 29, pp. 392-409.


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pp. 305. Subramanian, A. and Nilakanta, S. (1996), “Organizational Innovativeness: Exploring the Relationship between Organizational Determinants of Innovation, Types of Innovations, and Measures of Organizational Performance”, Omega International Journal of Management Science, Vol. 24, No. 6, pp. 631-647. Waddell, Dianne & Sohal, Amrik S. (1998), “Resistance: A constructive tool for change management”, Management Decision, Vol. 36, No. 8, pp 543-548, MCB University Press. APPENDIX A This Appendix reproduces the questionnaire used in this survey. Score: 1) Strongly Disagree, 2) Somewhat Disagree, 3) Neutral, 4) Somewhat Agree, 5) Strongly Agree Questions: To which degree do you agree with the following statements? 1 1.1 1.1.1 1.1.2 1.1.3 1.1.4 1.1.5 1.2 1.2.1 1.2.2 1.2.3 1.2.4 1.2.5 1.2.6 1.2.7 1.2.8 1.2.9 1.3 1.3.1

Organizational Climate Risk orientation The philosophy of your management is that in the long run we get ahead playing is slow, safe, and sure. The business of your organization has been built up by taking calculated risks at the right time. Decision making is too cautious for maximum effectiveness in your organization. Your management is willing to take a chance on a good idea. It is necessary to take some pretty big risks occasionally to keep ahead of the competition in the business you are in. External orientation The business objectives of your organization are driven primarily by customer satisfaction. Your organization constantly monitors its level of commitment and orientation to serving the customer needs. The strategy for competitive advantage of your organization is based on the understanding of customer needs. The strategies of your organization are driven by the organization’s beliefs about it can create greater value for customers. Your organization measures customer satisfaction systematically and frequently. Your organization gives close attention to after-service contact with the customers. Employees freely communicate information about their successful and unsuccessful customer experiences across all business functions. All of the business functions in your organization are integrated in serving the needs of target markets. All of your managers understand how everyone in the organization can contribute to creating customer value. Achievement orientation Achievement of goals has a very important place in your organization.

Score


Score: 1) Strongly Disagree, 2) Somewhat Disagree, 3) Neutral, 4) Somewhat Agree, 5) Strongly Agree 1.3.2 Being the leaders in the industry sector is very important in your organization. 1.4 Organizational slack 1.4.1 There is generally no scarcity of financial resources for capital projects in your organization. 1.4.2 There is usually abundant availability of required labour skills within your organization. 1.4..3 There is usually no shortage of managerial talent to operate your organization effectively. 1.4.4 The amount of funds already committed for capital projects is a large proportion of the available financial resources in your organization. 2 2.1 2.1.1 2.1.2 2.2 2.2.1

2.2.2

2.3 2.3.1 2.3.2

3 3.1 3.2 3.3 3.4 3.5

Organizational Characteristics Formalization Compared to other organizations in your areas, your organization extensively use written job description for all classes of employees. Compared to other organizations in your areas, your organization extensively uses written policies and procedures to guide the actions of employees. Centralization When an operating department produces results that deviate from its plans, the instructions to take appropriate corrective actions usually come from top managements rather from the operating department itself. Consider a recent project undertaken by your organization that required setting up a special task force. There may have been situations when this task force encountered deviation from what was planned. During these situations, the instructions to take corrective action usually came from top managements rather from the operating department itself. Specialization Employees in your organization are seldom transferring across departments. Your organization hire individuals that fully meet the requirements for specific technical skills in each functional area rather hire individuals with general skills and then train them in-house in functional areas. Learning Abilities Your organization regularly revisits its vision and strategic framework to ensure the organization is carrying out faster learning. Your organization has defined learning targets that are challenging but attainable. Employees in your organization understand how their learning contributes to the organization’s success and the learning is linked up with appropriate rewarding systems. When a learning target is achieved, no matter how small, your organization will celebrates and rewards the employees who succeed. Your organization devises and implements a full-scale collaborative-coaching plan with learners who have a negative view of their learning abilities.


3.6

3.10

Your organization has formed project teams to identify improvement opportunities and define improvement actions. Your organization has chosen a champion to closely monitor tasks of a learning target and convene the respective group whenever necessary to ensure achieving the target. As soon as one target has been met, set another. Your organization continuously benchmark its learning processes against that of other organizations. Your organization uses technology to its greatest advantage for creating learning, reframing the business as necessary, and providing interactive learning as well as for documenting, expending, speeding up, transferring, and reinforcing learning. Your organization creates its future by changing the ground rules for the industry.

4 4.1 4.1.1 4.1.2 4.1.3 4.1.4 4.1.5 4.1.6 4.1.7 4.1.8 4.1.9 4.2 4.2.1 4.2.2 4.2.3 4.2.4 4.2.5 4.2.6 4.2.7 4.2.8 4.2.9 4.2.10 4.2.11 4.2.12 4.2.13 4.2.14 4.2.15 4.2.16 4.2.17

Innovativeness (Year of Adoption “N” - not adopted, “NA” - not applicable) Technical Innovations Computerized manufacturing system Computerized production scheduling or project management system Web based ordering system Web based customer services or feedback system Computerized product design system Electronic data interchange (EDI) with customers Electronic data interchange (EDI) with suppliers Computerized logistic management Point of sale (POS) system Administrative Innovations Formal strategic plan of innovation Management by objective Continuing education programs for employees Job rotations Special tasks force for ad-hoc problems Incentive/reward systems for officers Incentive/reward systems for non-officers Formal feedback system for customers Electronic mailings (email) Computerized workflow management Automated fax transmissions Computerized human resources management Computerized customer billing Computerized sales forecasting Computerized end product inventory forecasting Organization Internet web site Remote system access

3.7

3.8 3.9



How do Organizations Implement Downsizing? – An Australian and New Zealand Study Franco Gandolfi Cedarville University E-Mail: [email protected]

ABSTRACT The Australian and New Zealand banking industries have been cutting their workforces steadily since the mid-1990s. With further rounds of workforce downsizing predicted, it was of considerable interest and importance to examine the implementation strategies that large Australian and New Zealand banks have adopted in their latest downsizing endeavors. This study has revealed three major findings. First, Australian banks tended to primarily adopt workforce reduction strategies, whereas New Zealand banks employed a mixture of organization redesign strategies, workforce reduction strategies, and systemic strategies. Second, Australian banks were perceived to have considerable depth in their downsizing, whereas New Zealand banks had more breadth in their overall strategies. Third, Australian banks favored to adopt reorientation approaches, whereas New Zealand banks were more inclined to embrace reinforcement (convergence) approaches. It remains unclear as to why large Australian and New Zealand banks have diverged in their approaches and strategies to downsizing and in their differing selection of available implementation strategies. Government interference, executive remuneration, industrial relations demands, competitive national and international market pressures, and the downsizing history of individual industries and organizations, on the one hand, and differences in national cultures and cultural values on the other, may have influenced the adoption of downsizing implementation strategies. At the same time, it has also been shown that downsizing has engendered negative financial, organizational, and social consequences in both Australia and New Zealand. Key words: Downsizing, implementation strategies, banks

INTRODUCTION Since the early to mid-1980s, organizational downsizing has become an omnipresent feature of a multitude of corporations and governmental agencies throughout the industrialized world (Littler, 1998). The prime catalyst for the majority of downsizing activities is the objective of a reduction of costs (Cascio, 1993), an increase of an organization’s levels of efficiency, effectiveness, productivity (Gandolfi, 2002), and competitiveness (Cameron, 1994), and thus an organization’s overall performance (Thornhill & Saunders, 1998). Therefore, the major raison d’être of any downsizing endeavor is to make an organization more competitive compared to its rivals (De Vries & Balazs, 1997). Empirical and anecdotal evidence suggest that the financial,


organizational, and social consequences of downsizing are largely negative (Morris, Cascio, & Young, 1999). Littler, Dunford, Bramble, and Hede (1997) assert that the after-effects of a downsizing affect the entire organization and its workforce in a most profound manner. There is also mounting evidence that suggests that organizations commenced downsizing efforts with inadequate plans, policies, and programs in place (Appelbaum, Delage, Labibb, & Gault, 1997), were ill-prepared for the aftermath of downsizing (Gandolfi, 2001), and severely neglected the employees that remained within the organizational system (Doherty & Horsted, 1995). The downsizing of organizational workforces is not a business phenomenon of the recent past. Rather, it has maintained and even increased its popularity and pervasiveness as a deliberate restructuring strategy in all industries (Morris et al., 1999), across the world (Dolan, Belout, & Balkin, 2000), and into the new millennium (Baruch & Hind, 2000; Lamsa & Takala, 2000; Gandolfi, 2003). Given the apparent absence of positive outcomes from downsizing (Cascio, 1993), the frequency of negative implications following downsizing (Morris et al., 1999), the ongoing popularity of downsizing (Harrison, 2000; Gandolfi, 2003), and the assertion of scholars that downsizing is still regarded as an understudied business phenomenon (Luthans & Sommer, 1999), this study aims to examine the adopted downsizing implementation strategies of large banks in Australia and New Zealand. The structure of this research paper is threefold. First, it reviews the literature on downsizing implementation strategies and presents the main research question. Second, it determines the implementation strategies that large Australian and New Zealand banks adopted in their last round of downsizing by means of the case-study methodology. Last, it analyzes and discusses the empirical findings derived from in-depth interviews. DOWNSIZING IMPLEMENTATION STRATEGIES The downsizing literature reveals that a number of distinct implementation strategies have been identified. Cameron, Freeman, and Mishra (1991, 1993) have conducted one of the most extensive and systematic studies of corporate workforce downsizing and reported three major findings regarding downsizing implementation strategies. First and foremost, they identified and differentiated between three distinct types of downsizing implementation strategies. That is, a workforce reduction strategy, an organization redesign strategy, and a systemic strategy. An overview of the downsizing implementation strategies is exhibited in Table 1.

Table 1 Downsizing implementation strategies Workforce reduction strategy Focus Target Implementation time Temporal target Inhibits

Workers People Quick Short-term payoff Long-term adaptability

Organization redesign strategy Jobs and units Work Moderate Moderate-term payoff

Culture Status quo processes Extended Long-term payoff

Quick payback

Short-term cost savings

Systemic strategy


Workforce reduction strategy

Organization redesign strategy

•Natural attrition •Abolition of functions •Hiring freeze •Merging of units •Early retirement •Job Redesign Examples •Buyout packages •De-layering •Layoffs •Reducing overall work hours •Retrenchments Source: adapted from Cameron et al. (1991, 1993)

Systemic strategy •Staff involvement •Simplification of processes •Bottom-up change •Continuous improvement

The workforce reduction strategy, often referred to as the “layoff strategy” (Ryan & Macky, 1998: 38), concentrates primarily upon the elimination of headcount and the reduction of the overall number of employees. It encompasses activities, such as layoffs, retrenchments, natural attritions, early retirements, hiring freezes, golden parachutes, and buyout packages (Cameron et al., 1991; 1993). This strategy is frequently implemented in a reactive manner as a cost-cutting measure and may serve as a short-term response to declining profits (Ryan & Macky, 1998). According to Cameron (1994), such “grenade-type” (p 198) approaches to downsizing are rarely successful and tend to be negative in their consequences. The organization redesign strategy focuses predominantly upon the elimination of work, rather than reducing the number of employees (Luthans & Sommer, 1999). It encompasses activities, such as abolishing functions, eliminating hierarchical levels (de-layering), groups, divisions, products, redesigning tasks, consolidating and merging units, and reducing overall work hours. Organization redesign strategies are commonly regarded as being difficult to implement quickly as this requires some advanced analysis of the areas concerned (Cameron et al., 1991). The systemic strategy is fundamentally different from the former two strategies in the sense that it appears to embrace a more holistic view of organizational change. Thus, downsizing ought to embrace all dimensions and aspects of the organization, including suppliers, customer relations, production methods, design processes, and inventories (Cameron, 1994). Systemic strategy focuses primarily upon changing the organization’s intrinsic culture and the attitudes and values of its employees (Luthans & Sommer, 1999). Hence, downsizing is viewed as “a way of life” (Filipowski, 1993: 1) and an on-going, continuous, and incremental process (Cameron et al., 1991). Within this framework, employees are not seen as the primary target of downsizing, but considered to be resources in an attempt to produce and incorporate downsizing ideas (Cameron, 1994). Cameron and his associates have also compartmentalized downsizing on the basis of the depth and breadth of available downsizing strategies. This is depicted in Table 2.


Table 2 Depth and breadth of downsizing Increasing depth

Increasing breadth

Workforce reduction strategy •Natural attrition •Layoffs/retrenchments •Early retirements •Buyout packages Source: adapted from Cameron et al. (1991, 1993)

Organization redesign strategy •Layer elimination •Unit combination •Product removal •Process rearrangement

Systemic strategy

•System analysis •Culture change •Bottom design

According to Cameron et al. (1991), organizations that incorporate a greater number of actions of the same category of implementation have more depth in their overall downsizing strategy. Conversely, organizations that employ a variety of strategy types have more breadth in their strategy. The results of a four-year study of 30 American organizations that had engaged in downsizing activities have disclosed that organizations were generally more likely to have depth rather than breadth in their overall strategy. This revelation can be attributed to the fact that most downsized organizations embarked upon workforce reduction alternatives rather than employing a multiplicity of downsizing strategies (Cameron, 1994). Two archetypal approaches to downsizing have emerged – reinforcement and reorientation. These approaches were originally developed and empirically tested by Freeman (1994), who had labeled these concepts “convergence” and “reorientation” (p 214). The approaches of reinforcement and reorientation are built upon differing models of organizational change. The concept of reinforcement (convergence) embraces the notion of an evolutionary, incremental, and gradual change model. As a consequence, reinforced or converged downsizing would be implemented on a smaller scale and as part of a process aimed at reinforcing an organization’s mission, strategy, systems, and structure (Ryan & Macky, 1998). The concept of reorientation, in contrast, encompasses the notion of a revolutionary, metamorphic, and discontinuous change model. Thus, reoriented downsizing would be implemented on a larger scale, with major redefinitions of an organization’s mission, strategy, and structure (Cameron et al., 1993). The two contrasting approaches are depicted in Table 3. Having reviewed the existing downsizing implementation strategies, the underlying research question of this study was to examine what main downsizing strategy or strategies large Australian and New Zealand banks implemented in their last round of downsizing.


Table 3 Reinforcement and reorientation approaches Reinforcement (convergence) approach

Reorientation approach

•Incremental downsizing and redesign

•Discontinuous downsizing and redesign

•Lower-level, less radical approaches

•Higher-level, more radical approaches

•Stability in management, technology, and systems

•Change in management, technology, and systems

•Changes in work, instead of structure

•Changes in structure, instead of work

•Reinforces mission and strategy

•Redesign mission and strategy

•Focus upon doing things better

•Focus upon doing different things

•Emphasis upon efficiency criteria

•Emphasis upon effectiveness criteria

•Downsizing precedes redesign Source: adapted from Cameron et al. (1993)

•Redesign precedes downsizing

LARGE BANKS IN AUSTRALIA AND NEW ZEALAND Downsizing has occurred throughout the industrialized world (Ryan & Macky, 1998), affected blue and white collar workers (Littler et al., 1997), targeted lower-level workers, professionals, middle managers, and higher-level workers (Littler, 1998), and permeated all industries (Morris et al., 1999). The banking sector has been particularly affected by the deregulation of the finance industry in both Australia and New Zealand. Some of the more notable repercussions have been workforce layoffs, redundancies, retrenchments, early retirements, buyout packages, golden handshakes, and branch closures. In Australia, for example, the size of the overall workforce in the finance industry has been rapidly declining since the early 1990s (Finance Sector Union, 2002: 4). According to the Australian Bureau of Statistics (ABS) (1998), the workforce of the Australian finance industry declined by 8.8 % between 1991 and 1996. This development was exacerbated by the fact that the implementation of downsizing in the Australian finance industry has proceeded and further rationalization activities have been predicted (Finance Sector Union, 2002: 4). In a similar vein, Harrison (2000) opines that the downsizing of Australian banks is not a phenomenon of the past and predicts that downsizing will remain a principal strategic managerial tool for the major banking institutions (Harrison, 2000). The New Zealand banking industry has also undergone significant structural, political, and technological changes since the commencement of the deregulation of the finance industry in the late 1980s. In line with developments in Australia, the workforce of the New Zealand banking industry has been steadily declining since the mid-1990s. Anecdotal evidence suggests that all major banks have had at least one round of workforce downsizing since the late 1990s and most large banks are currently considering further reductions in workforce. The author of this report was actively involved in the execution and implementation of two separate downsizing activities in large New Zealand banks in 2001 and 2002. A relatively recent report from a New Zealand governmental agency revealed that up to two thirds of all finance jobs could potentially disappear by the year 2015 due to projected restructuring activities and consolidations (New Zealand Banking Review, 2003).


Having surveyed the literature and examined some of the recent developments of workforce levels in the Australian and New Zealand banking industries, the fundamental question arises as to whether there may be differences in the way banks execute downsizing. In other words, do Australian and New Zealand banks differ in their adoption of downsizing strategies and in their depth and breadth of downsizing? Do contextual and cultural differences result in differing downsizing strategies? Are organizations in certain cultural environments more likely to favor specific downsizing strategies? Are differences in national cultures reflected in organizational decisions about downsizing? Hitherto, no comparative studies on possible similarities and dissimilarities between two different countries and their downsizing strategies have been documented. Analyzing the Australian and New Zealand national cultures and determining the cultural similarities and divergences in greater detail is beyond the scope of this paper. However, given the progression of deregulation, the composition and national importance of the banking sectors, and the geopolitical interdependence of both countries, it was expected that the findings would depict a consistent and convergent picture. CASE STUDY METHODOLOGY Academic research on downsizing should adopt an inductive theory-building rather than a deductive theory-testing approach (Cameron et al., 1993; Ryan & Macky, 1998). This judgment corresponds with Littler (1998), Morris et al. (1999), and Dolan et al. (2000). As a consequence, this study has employed the case study methodology. Case study research is essentially a form of “empirical inquiry” (Yin, 1994: 23). According to Yin (2003), the case study method focuses upon a phenomenon within its real-life context by obtaining data from a multitude of sources in order to comprehensively investigate and analyze the phenomenon in-depth. Thus, the case study method has the capacity to generate theory (Yin, 2003). The selection of cases in qualitative case study research is purposeful (Perry, 1998) and involves the use of replication rather than sampling logic (Eisenhardt, 1989; Yin, 1994; Carson, Gilmore, Gronhaug, & Perry, 2001). Furthermore, the selection of individual cases depends largely upon the conceptual framework developed in the literature review and prior theory (Perry, 1998). The ultimate underlying principle of the selection procedure is selecting “information rich cases” (Patton, 1990: 181). According to Stake (1994), the importance of information richness (Patton, 1990) exceeds the issue of representativeness. This study has purposefully selected eight study cases – the four largest Australian and the four largest New Zealand banks. The research has exclusively involved large banks, as measured by the total number of employees (Robbins, 1983). The eight banks are considered the key players in their respective industries and countries. The decision to involve large organizations was due to Keller’s (1998) observation that “it is the large companies that appear to have been the prime targets of organizational downsizing” (Keller, 1998: 324). A considerable number of in-depth, face-to-face interviews and teleconferences with senior, middle, and operational managers of the eight study cases were conducted between October 2003 and March 2004. The administrative titles of the key informants included Chief Executive Officer (CEO), Chief Operations Officer (COO), Chief Knowledge Officer (CKO), Director HR, Director L&D, Manager L&D, and HR Manager. The distinction between executive, middle, and lower-level management was critical to the success of the study and satisfied the requirement of conducting interviews at different hierarchical levels within all case study organizations (Perry,


1998; Carson et al., 2001). The qualifying criteria for all involved participants were (1) the status of being a downsizing ‘survivor’ (Noer, 1993) and (2) the status of being a downsizing ‘driver’ (Dolan et al., 2000). In other words, participants needed to have served the downsized organization prior to, during, and after the downsizing and must have been actively involved in the actual planning, development, and execution of the downsizing endeavor. There was an underlying expectation that participants would provide information that would in turn have the capacity to build theory. Thus, participants were seen as “informants” (Bogdan & Biklen, 1998: 32) rather than mere “respondents” (Yin, 1994: 84). All managers were interviewed only once over the six-month period with each interview lasting from one to one and a half hours. The interviews were focused (Adams & Schvaneveldt, 1991) in nature. This allowed the interviewer to probe far beyond the answers to the prepared and standardized questions (Berg, 1989). With the consent of the participating organizations and individual managers, each interview was taped and meticulously transcribed and documented. The interview transcripts constituted the main raw material (Silverman, 1997), and provided “highly detailed and publicly accessible representations of social interaction” (Silverman, 1997: 203). A total of thirty-six participants across all eight study cases were interviewed - twelve executive managers, twelve middle managers, and twelve operational managers. The overall figure was consistent with the case study literature that suggests the number of conducted interviews to be in the range of 20 to 50 participants (Larsson, 1993; Perry, 1998). RESULTS AND DISCUSSION This case study ascertained the downsizing implementation strategies of large Australian and New Zealand banks. It also sought to determine patterns, consistencies, and anomalies in regard to the implemented downsizing strategies among and between the main banks. Three key findings have emerged. First, the study has shown that all participants declared that their respective organization has engaged in workforce downsizing practices since the early days of this millennium. The vast majority of Australians stated that workforce reduction strategies, including workforce layoffs, retrenchments, early retirements, buyout packages, natural attritions, and hiring freezes, were the most commonly utilized downsizing strategies and adopted without restraint in the most recent round of downsizing. A considerable number of participants indicated that layoffs and staff retrenchments were frequently seen as the bank’s “first preference”. In this sense, participants understood that workforce reduction strategies were likely to have a quick implementation time with short-term payoffs. In contrast, organization redesign strategies, including job redesign, merging of units, abolition of functions, and delayering, were not seen as primary strategies. Rather, these secondary strategies were seen as a direct consequence of the primary downsizing implementation strategies. In other words, in an Australian context, organization redesign strategies were utilized only in response to and as a direct consequence of the adoption of workforce reduction strategies. The systemic strategy, that views downsizing as ‘a way of life’, was rejected by all Australian managers. Participants perceived systemic strategies to inhibit short-term savings and to only engender long-term payoffs. Thus, systemic strategies were not seen as suitable implementation strategies.


In stark contrast to Australian banks, New Zealand bank managers perceived organization redesign strategies to be the preferred downsizing implementation strategy. According to the New Zealand participants, the primary focus of any downsizing endeavor should be “work” rather than “people”. In other words, the emphasis should lie with the elimination of work rather than reducing the number of employees in the first instance. Participants nominated the redesign of tasks and the consolidation of work, units, products, groups, and divisions as the standard practices in downsizing efforts. However, New Zealand managers stressed that the adoption of organization redesign strategies necessitated a profound level of understanding of the individual operations and tasks and also required some advanced analysis of the targeted areas. Workforce reduction strategies were seen as a “last resort”. They were also viewed to inhibit long-term adaptability and perceived to be “extremely disruptive” and “damaging to the image, ethos, and culture of the organization”. At the same time, New Zealand managers admitted that a number of workforce reduction strategies, including specific hiring freezes, natural attritions, and limited retrenchments, were embraced in the last round of downsizing. New Zealand participants also stated that even though a systemic strategy per se, with its focus on culture, was not adopted, some distinct elements of a systemic strategy were nevertheless actively being pursued, including, continuous improvement, staff involvement, and bottom-up change. Second, this research has revealed that there were differences in the breadth and depth of downsizing implementation strategies between Australian and New Zealand banks. Australian bank managers generally resorted to workforce reduction strategies as primary downsizing implementation strategies and largely forfeited the options of organization redesign strategies and systemic strategies. More specifically, all Australian study cases reported the adoption of layoffs, retrenchments, early retirements, natural attritions, hiring freezes, and early buyouts. Moreover, these strategies were utilized by all Australian banks in their last round of downsizing. Thus, Australian banks showed great depth in their downsizing. In stark contrast, New Zealand bank managers tended to embrace a more holistic approach to downsizing and resorted to a broader variety of implementation strategies. According to the participants, downsizing strategies comprised (1) the primary tools of redesigning tasks and consolidating of work, units, products, groups, and divisions, (2) the secondary tools of hiring freezes, natural attritions, early retirements, voluntary redeployments, and voluntary separation packages, and (3) the “last resort” tools of involuntary redeployment, retrenchments, and layoffs. At the same time, participants declared that systemic strategies, such as continuous improvement, bottom-up change, and staff involvement, were also pursued and implemented. Thus, New Zealand banks showed great breadth in their downsizing. Third, the study has shown that Australians had a tendency to embrace “reorientation” (Cameron et al., 1993) approaches to downsizing, whereas New Zealand bank managers were more likely to adopt “reinforcement” (Cameron et al., 1993) or “convergence” (Freeman, 1994) approaches. More specifically, Australians tended to engage in radical, high-level approaches, in that significant change to mission, strategy, structure, systems, and technology occurred in the last round of downsizing. Participants viewed the approach to change to be “discontinuous”. The last round of downsizing was also implemented on a larger scale with major redefinitions. However, New Zealand participants incorporated less radical and lower-level approaches in their last round of downsizing, seeing it as a way to “reinforce mission and strategy” and stability in management, systems, and technology. There also seemed an emphasis upon changes in work


rather than people. Participants perceived the approach to downsizing to be “incremental” and “gradual”. Participating managers stated that the last round of downsizing was implemented on a smaller scale and as part of a continuing process. An overview of the three main findings in regards to comparative inter-countries downsizing strategies is exhibited in Table 4. Table 4 Overview of comparative inter-countries downsizing strategies Australia New Zealand Implementation strategies

Mostly workforce reduction strategies

Mostly organization redesign strategies

Breadth/Depth in overall downsizing

More depth in overall downsizing

More breadth in overall downsizing

Reorientation approach

Reinforcement approach

Approach to downsizing Source: analysis of field data

CONCLUSION This study examined the adopted downsizing implementation strategies of large Australian and New Zealand banks. At the outset of the research, the study reviewed the literature on downsizing implementation strategies and presented the research question. The adoption of the case study methodology enabled the researcher to analyze and determine the implementation strategies adopted by large Australian and New Zealand banks in their last round of downsizing. Following the processes of data gathering, analysis, and interpretation, three major findings emerged. First, Australian banks tended to primarily adopt workforce reduction strategies, whereas New Zealand banks had a mixture of organization redesign strategies, workforce reduction strategies, and systemic strategies. Second, Australian banks were perceived to have considerable depth in their downsizing, whereas New Zealand banks had more breadth in their implementation strategies. Third, Australian banks tended to adopt reorientation approaches, whereas New Zealand banks were more inclined to embrace reinforcement or convergence approaches. Prior to this study, there was little comparative data on downsizing implementation strategies between and among competitors, industries, and countries available. Given the progression of deregulation, the composition and national importance of the banking sectors, and the geographical and geopolitical interdependence of both countries, there was an implicit expectation that the cross-comparison of implementation strategies would show a relatively convergent picture. However, this study has shown that the differences in the adoption of downsizing strategies between Australian and New Zealand banks were considerable. This poses a multitude of questions. For example, do the results show a general pattern? How can the similarities and dissimilarities be specifically explained? How do the results compare to other comparative cross-sectional and cross-cultural studies? In the absence of an established framework and the apparent lack of comparative cross-cultural data, the task of providing a clear conclusion is problematic. It remains unclear as to why large Australian and New Zealand banks have diverged in their approaches and strategies to downsizing and in their differing selection of available implementation strategies. Possible explanations are manifold - government interference, executive remuneration, industrial relations demands, competitive national and international market pressures, and the downsizing history of individual industries and


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The Role of Personality Traits in UTAUT Model under Online Stocking Hsing-I Wang Overseas Chinese Institute of Technology, and National Cheng-Chi University, Taiwan, E-Mail: [email protected] Heng-Li Yang National Cheng-Chi University, Taipei, Taiwan, E-Mail: [email protected]

ABSTRACT The introduction of a new science and technology will fully reflect its value and its potential to create value only when individuals are willing to accept and adopt it in their daily works. The theory of acceptance and use of new technology has been widely discussed for decades and is still attracting scholars to work toward developing a comprehensive model. The reasons are because of various latent variables that might affect the model, and moreover, the way how the variables interfere the model has not reached an agreement. This research combines the theory of personality traits with the unified theory of acceptance and use of technology. The purposes are to examine the roles that personality traits play in UTAUT model under the context of online stocking. Keywords: Personality Traits, Big-Five Model, UTAUT Model, Online Stocking INTRODUCTION The introduction of a new science and technology will fully reflect its value and its potential to create value only when individuals are willing to accept and adopt it in their daily works. After the Technology Acceptance Model (TAM) was presented, the model was either refined or modified. In addition, several other similar models and theories were established to explain why an individual would adapt himself to a new technology, and in turn, what actions an organization should take to facilitate the use of that technology. Literature surveys indicated that in the efforts of understanding the drivers of acceptance, researcher sometimes needed to choose a favored model from many competing models as well as appropriate variables across models. Venkatesh et al. (2003) then proposed the Unified Theory of Acceptance and Use of Technology (UTAUT) that include eight different models in order to get an integrated view of user acceptance. Nevertheless, it is our belief that some important constructs are still missing in the context of online stocking. Among those constructs that could be added to predict the intention, this research focuses on personality traits. Ajzen had taken the relationships between personality traits, behavior and attitude into consideration while he was developing the Theory of Reasoned


Action (TRA) theory in 1988, and proposed that personality traits must have some indirect influence on a person’s behavior (Ajzen, 1988). Other literature surveys have also identified the close relationships between human behavior and personality traits. Nevertheless, personality traits have never been explicitly examined in TAM or any other related mode. This research aims at clarifying the affects that personality traits may convey. Online stocking was chosen to be the area to study with due to the following reasons. (1) The rise of the internet has lifted the great waves in the industry. For investors, the demands of faster, more convenient, more elastic investment channel, and the immediate accurate information are magnified as well. However, the populations of using online stocking have not increased to an edge as expected. The reasons of hindering the acceptance of using the new technology are worth being delved. (2) Issues of online stocking are similar to online shopping. It is suggested in this paper that research results on online consuming can be borrowed to study online stocking. (3) Although all transactions are also on the Internet, online stocking has more risks comparing to online shopping. It is noticed that nearly no researches that have addressed personality traits versus intentions under consciousness of risk. There are two objectives in this research. First, we hope to examine the role personality traits in UTAUT model: would they be external variables or moderators? Second, it is expected that valuable insights would be obtained from this research, and in turn, to provide financial companies appropriate suggestions to make marketing strategies. The Big Five Factors is adopted in this research to explain different types of personalities. The Big Five Factors had been applied to various domains after it was formed (McCrae and John, 1992). Research subjects include the relationship of personality traits and job satisfaction, personality traits and the possibility of suffering a certain kind of disease, personality traits and exercise training program, etc. This research focuses on personality traits and the acceptance and use of a new technology in financial area. In the following sections, this paper first introduces the concept of the Big Five Factors and the UTAUT model. Two research models will present after introducing the methodology. The results of data analysis are interpreted and discussed. Conclusions are then given in the last section. LITERATRUE SURVEYS The Big Five Factors Personality determines the unique thinking and behaving patterns of an individual (Allport, 1961). Traits, however, are the degree of this emerged uniqueness when an individual is observed from different angles or dimensions. Most psychologists also agree that human behaviors relate to personal factors as well as the context (Allport, 1961, Endler & Magnusson, 1976). Eysenc (1991) proposed that personality traits contain five principles, namely replicability, comprehensiveness, external correlates, source traits and multiple levels. The five principles were then recognized as Five Factor Model (FFM) or Big Five Factors. FFM categorized personality traits into Extraversion (E), Conscientiousness (C), Agreeableness (A), Neuroticism (N) and Openness (O). High Extraversion persons are mostly positive, optimistic, are willing to take risks, like to be around crowds, have more social activities, and tend to look for amazement. Conscientious persons are more authoritative, meticulous, responsible, and tough. Persons, who are more agreeable, are cordial, enthusiastic, will sympathize with or help others. High Nervousness persons are relatively unstable, easily to be frightened, rash, depressive


and angry, etc. Theoretically, the person of the nervousness type is apt to exercise a certain behavior under the social pressure. The style of openness refers to the abilities to accept various experiences, cultures, always express one’s curiosity and has much more imagination. While TRA theory was under developing, Ajzen thought that the personality traits should only be the external parameters. Together with other external variables, they would change a person's faith and motive, and then influence the attitude and subjective norm (Ajzen, 1988). TRA explained the personal behavior that is always volitional, however, from time to time and under some certain circumstances, behaviors are considered more involuntary. Therefore, Ajzen proposed TBP model and added the new construct of perceived behavioral control (Ajzen, 1991). Perceived behavioral control was further divided into internal and external control. Internal control refers to an individual’s self-perception to the resources that he owns. These perceptions could be heavily influenced by one’s personality. Courneya et al. (1999) also added personality traits in TPB model and tried to prove that personality traits would affect behavior intentions through attitude, subjective norm and perceived behavioral control. However, their research model failed to explain the effects of personality traits on intentions completely. Moreover, Rhodes et al. (2002) considered personality as moderators in their research. Online Stocking Online stocking has been recognized as an important mean to conduct investment under the trend of globalization economy. Online stocking is simple and convenient, its transaction is fast, its cost is relatively low, and it can offer other value-added financial information services. For investors, online stocking offers favorable discount of the service charge; has much more privacy and security; provides much more flexibilities to manage the time, etc. The dealers in securities have tried to offer multiple favorable services to potential customers. However, by the end of 2002, the population of online stocking was only 15 % of the total security investors in Taiwan (Find, 2002). Jeng (2002) found that investors perceived online stocking as one of the activities on the Internet. Online activities are considered boring, lacking of interactions with people, less trust and more risks. For those who are active on consuming online are mostly aggressive, adventuresome, enjoying competition and are always fascinated by newish (Swinyard & Smith, 2003). In contrast, people who are more conservative or conscientious, tend to be more prudent before they take actions. Still, the situation might be able to be changed if businesses would offer a new design or a new way of doing business (Jahng et al., 2002). UTAUT Basically, investments take a lot of risks. Whether investors are willing to adopt online stocking depends on the degrees of their acceptances of the new technology. TAM model believes that usefulness and easy to use are the two determinants for an individual to accept a new technology. Longitudinal researches observed the same subjects from various dimensions and developed several different models. Venkatesh and Davis (2000) believed that factors such as personal image and the relevance of jobs would affect the perceived usefulness; they proposed a revised model TAM2 to include a new construct named social influence. Thompson, Higgins and Howell (1991) added two more variables including the long-term effects of new technology and facilitating conditions while exploring users’ behaviors on using PC. The main purposes of these researches were trying to assist companies to understand how consumers and employees


would react to the introduction of a new technology. Nevertheless, previous researches were mostly limited to some certain dimensions or constructs. As a result, companies were not able to get an entire view of the reasons why customers or employees resisted the acceptance of a new technology. Venkatesh et al. (2003) therefore examined eight prominent models and proposed the integrated one. UTAUT consisted of four constructs that were extracted from the eight models and would definitely affect the intention of behavior. The four constructs are performance expectancy, efforts expectancy, social influence, and facilitation conditions. The relationships between personality traits and some of the four constructs have been separately discussed in the previous researches. For instance, researches concerning personality traits on performances found that the two variables are positively related (Connolly & Viswesvaran, 2000, DeNeve & Cooper, 1998, Judge et al., 2002). Gellatly (1996) examined the impact of a single trait “Conscientiousness” on job performance and found that performance expectancy was the intermediary between personality trait and job performance. The research findings suggested that conscientious persons believe that they can perform superior in their jobs and in turn, they set higher expectancy and work harder to achieve that target. The intermediary relationship did not, however, emerge from Barrick and Mount’s (1991) research. The research assumed that high nervousness persons were easily to be eliminated from their positions and hence were not able to give enough time to observe the impacts of their characteristics on job performances. Moreover, the applications of FFM to medical researches also proved that once personality traits were classified appropriately, they could be used to predict human behaviors (Courneya et al., 2002. Hough, 1992).These facts add more values to this research to explore the role of personality traits in UTAUT. The Combination of Personality Traits and UTAUT Moderators have got great attentions in MIS field. And as the interests on moderated relationship increased, researchers also found that: context matters in MIS researches (Barrick & Mount, 1991). Previous researches have shown the latent relationship between personality traits and the acceptance of new technology, only that it has been never included explicitly in the model. How the personality traits would affect the intention to accept a new technology has not reached final conclusions. As indicated before in this paper that human behaviors relate to personal factors and the context, this research focuses mainly on the context of online stocking, exploring the role that personality traits play on UTAUT model: indirect or intervening. METHOD AND DATA ANALYSES Research Model and Hypotheses Based on the findings of literature surveys, this research has the following observations. (1)Since personality traits may dominate a person’s behavior, the effects of personality traits on the intention of behavior will be considered in this research context. (2)Some researches indicated that personality traits influenced the intention of behavior through the intervening variables such as performance expectancy, social influences and facilitating conditions. In contrast, some other empirical studies also identified the moderating effects of personality traits on the intention of behavior. In other words, personality traits may enhance or weaken an individual’s willingness or attitude toward behavior. However, some researches were still not able to validate any relationship between the constructs. Moreover, effort expectancy was never


discussed in the previous researches. (3) Online stocking is full of uncertain risks. Learning how personality traits affect the behavior may benefit both investors and financial businesses. Performance expectancy, effort expectancy, social influence and facilitating condition are considered important constructs under the context of online stocking in this research. Due to the effects of personality traits on the intention of behavior are still pending, this paper proposes two research models in Figures 1 and 2.

Figure 1 Research model 1

Figure 2 Research model 2

Model 1 is hypothesized that personality traits will affect the intention of adopting online stocking indirectly through performance expectancy, effort expectancy, social influence as well as facilitating conditions. Model 2, however, is hypothesized that personality traits and the internet experience will moderate the effects of performance expectancy, effort expectancy, social influence, facilitating conditions on the intention of adopting online stocking. Detail descriptions of hypotheses are given in table 1. In order to focus on investigating the effects of


personality traits, UTAUT model has been simplified by removing all moderators but experience. Experience is also renamed as internet experience to fit the context of this research. Moreover, this research focuses only on behavior intentions. The actual behavior requires a certain period of time to observe and is thus not included in the models. Table 1 List of hypotheses Hypotheses

Description

H1a-H1e

Extraversion, Conscientiousness, Agreeableness, Neuroticism and Openness will influence the intention of adopting online stocking through performance expectancy, respectively.

H2a-H2e

Extraversion, Conscientiousness, Agreeableness, Neuroticism and Openness will influence the intention of adopting online stocking through effort expectancy, respectively.

H3a-H3e

Extraversion, Conscientiousness, Agreeableness, Neuroticism and Openness will influence the intention of adopting online stocking through social influence, respectively.

H4a-H4e

Extraversion, Conscientiousness, Agreeableness, Neuroticism and Openness will influence the intention of adopting online stocking through facilitating conditions , respectively.

H5

The influence of performance expectancy on the intention of adopting online stocking will be moderated by personality traits and internet experience.

H6

The influence of effort expectancy on the intention of adopting online stocking will be moderated by personality traits and internet experience.

H7

The influence of social influence on the intention of adopting online stocking will be moderated by personality traits and internet experience.

H8

The influence of facilitating conditions on the intention of adopting online stocking will be moderated by personality traits and internet experience.

Measurement and Instrument for Data The definition of each personality trait is adopted directly from Costa & McCare (1992, 1995); the familiarity with the Internet was defined by Novak & Hoffman (Novak and Hoffman, 1997). All the other variables in model 1 and model 2 remain the same as indicated in the UTAUT model. Details are given as follows. Performance expectancy (PE) is defined as the degree to which an individual believes that using new technology would help on improving his or her working performance. It is measured by the perceptions of using online stocking system in terms of the benefits, speed, usefulness and productivity. Effort expectancy (EE) is the degree of ease associated with the use of the system and is measured by the perceptions of ease of using or understanding the operations of the online stocking system. Social influence (SI) refers to the degree to which an individual perceives that important others believe he or she should use the technology and is measured by the perception that


other persons of importance or influence think that he or she should use the online stocking system. Facilitating condition (FC) refers to the degree to which an individual believes that an organizational and technical infrastructure exists to support use of the system and is measured by the perception of having required resources or facilities knowledge to use the online stocking system or having someone to get helps. Intention of adopting online stocking (INTEN) is the possibilities of using online stocking system. Measurements include the intension, plan or estimate of using the online stocking system in the future. Extraversion (E) is positive, optimistic, excited, is willing to take risks, and likes to be around crowds. It is measured by the degrees of positive affect, gregariousness, activity and assertiveness. Conscientiousness (C) refers to authoritative, meticulous, responsible, and tough. Measurements include the degrees of order, dutifulness, achievement-striving, self-discipline. Agreeableness (A) refers to cordial, enthusiastic, will sympathize with or help others and is measured by the degrees of trust, straightforwardness, altruism, compliance, and tendermindedness. Neuroticism (N) is unstable, easily to be frightened, rash, depressive and angry. It is measured by the degrees of anxiety, angry, depression and vulnerability. Openness (O) is easy to accept various experiences, cultures, always express curiosity and have much more imagination. Measurements include the degrees of fantasy, feelings, ideas, values, aesthetics and action. Internet experience (W) refers to the continuously and frequently use Internet for specific tasks and is measured by the time spending on and the frequency of using the Internet.

Table 2 shows the sources of questionnaires and their reliabilities and validities. All questions were translated into Chinese and were proofread by an English teacher. Two professors (with major in Finance and MIS, respectively) were invited to pretest the questionnaires. All questions were measured by 5-point scale ranging from 1 (strongly disagree) to 5 (strongly agree). To financial consulting companies or security businesses, any information concerning their clients would be extremely confidential. Therefore, it is impossible to get a list of investors to conduct a systematic sampling. In addition, the questionnaire respondents should have some investment experiences. So, without any filtering, online survey, e-mail questionnaires or interviewing people on street are deemed to be inappropriate. Consequently, through cooperation, the agents in eight major security companies were invited to help distribute the questionnaires to their clients.


Table 2 Sources of questionnaires Source of Reliabilit questionnaire y

Variables

Validity

UTAUT Constructs

Ventkatesh et al. (2003)

>0.7

Acceptable convergent and discriminant validity (Ventkatesh et al., 2003).

Extraversion

NEO-PI (form S) Costa & McCare (1992)

0.86

Acceptable convergent and discriminant validity (Barrick and Mount, 1991, Costa and McCrae, 1995, Eysenck, 1991, Narayanan, Menon and Levine, 1995)

Openness Agreeableness

0.81 0.73

Conscientiousness

0.77

Neuroticism

0.68

Internet experience

GUV’s WWW user surveys (1998)

0.58

NA

Data Analysis 700 questionnaires were distributed to investors who were not necessarily exercising online stocking. Of the 240 returned questionnaires, 44 were invalid. So, effective response rate is 28%. The invalid questionnaires include: incomplete answers, answers that were obviously conflict or answers that were the same to all the questions. Reliabilities and discriminant validities were reanalyzed with the returned data. Reliability of internet experience is 0.815. All internal consistency reliabilities except “Openness” and “Agreeableness” are greater than 0.7. The discriminant validity was calculated by examining all the Chi-square values of each pair of constructs (Anderson and Gerbing, 1988). Among the 45 pairs of comparisons, “Extraversion” vs. “Intention”, “Openness” vs. “Intention” and “Agreeableness” vs. “Intention” showed insignificant χ2 values. Table 3 Demographic of respondents sex

age

# of years on security investment

Has online investment experience

M

F

-20

2029

4049

50 +

-1

15

510

10+

yes

no

9 8

9 8

60

94

31

11

46

7 4

47

29

76

120

From Table 3, we noticed that 60 respondents were younger than 20. A lot of students had begun to invest on stocks or securities while they were taking financial courses in colleges. The majority respondents had 1 to 10 years experiences on stocks investment, and about 38% (76 responses) had already been buying stocks online. In the questionnaire, we further asked whether the online-experienced person would retain his/her behavior, 73 replied yes. On the contrary, only 2 persons who had no online experiences would try to adopt new means to engage in


investment.

Step 1

Step 2

Dependent variable Intention of adopting online stocking

Table 4 Results of indirect effects Independent variable Adjusted R2

Performance Expectancy

Efforts Expectancy

Social Influence

Facilitating Condition

Step 3

Intention of adopting online stocking

Extraversion Conscientiousness Agreeableness Neuroticism Openness Extraversion Conscientiousness Agreeableness Neuroticism Openness Extraversion Conscientiousness Agreeableness Neuroticism Openness Extraversion Conscientiousness Agreeableness Neuroticism Openness Extraversion Conscientiousness Agreeableness Neuroticism Openness Extraversion Performance Expectancy Extraversion Efforts Expectancy Extraversion Social Influence Extraversion Facilitating Condition Openness Efforts Expectancy Openness Social Influence Openness Facilitating Condition

.083

.216

.186

.044

.140

.357

β coefficient .216(**) 0.73 -.014 .008 .164(*) .351(**) .040 .060 .027 .123 .269(**) .042 -.054 -.133(*) .239(**) .209(*) .032 .115 .137 -.177(*) .220(*) .163 -.107 .001 .183(*) -.005 .605(**)

.330 .145 .399 .341 .205 .415

.036 .567(**) .187(**) .324(**) .076 .614(**) .113 .549(**) .309(**) .384(**) .148(**) .605(**)


Method proposed by Barron and Kenney (1986) was adopted in this paper to test the indirect effect. In the model, independent variables are personality traits; dependent variable is the intention of adopting online stocking. The mediators are PE, EE, SI and FC respectively. Step one in table 4 runs regression of “Personality traits” on “Intention”. The result shows that “Extraversion” (p