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ISSN 2250 - 0960 Listed in Ulrich’s Periodicals Directory © ProQuest, USA
Kushagra International Management Review (A bi-annual International Journal) Vol. 3
No. 2
November 2013
ISSN: 2250-0960 Kushagra International Management Review Vol. 3, No. 2 November, 2013
KU SHAGRA INSTITU TE OF INFORMATION & MANAG EMENT SC IENCE (K IIMS) An ISO 9001: 2008 Certified Institution Approved by AICTE, Ministry of HRD, Govt. of India Affiliated to Biju Patnaik University of Technology, Govt. of Odisha
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Preface Regulations are indispensable to the proper functioning of economies and societies. They underpin markets, protect the rights and safety of citizens and ensure the delivery of public goods and services. At the same time, regulations are rarely costless. In this environment of rapid change and what can seem like ever increasing demands, management often finds it difficult to fully comprehend the total cost of compliance. It sees the potential for costs to escalate without the organisation realising the full benefit of such investment. Additionally, there is the need to provide more relevant and timely information in the public arena. New levels of accountability, which come not just from new laws and regulations but also from the expectations of a broader stakeholder group, have elevated the concerns at board level of ensuring that effective, robust and reliable governance and compliance tools are in place and being utilised. In recent times there has been a paradigm shift in many economies in the way that corporate governance and business ethics are approached. It is a shift that continues to be driven by demanding performance expectations, increasing stakeholder demands and growing public scrutiny after some spectacular failures around the globe. For a large number of companies from different countries and the corporate governance plays a crucial role in efficient company monitoring and shareholder protection and consequently positively impacts valuation. Corporate governance appears more valuable for companies that rely heavily on external financing. In economy includes the full range of institutional, firm and entrepreneurial activities that are the foundation for creating value within society. Accompanying the obvious interest of policymakers, scholars are beginning to explore strategic and entrepreneurial activities occurring within the informal economy and the topic “Strategic Measures for Economic Governance and Regulation” has been chosen to give an insight towards the emerging issues of the day. All family members of Kushagra Institute of Information & Management Science (KIIMS) sincerely hope this bi-annual International Journal Vol. 3, No. 2, “Kushagra International Management Review” ISSN 2250-0960 with its contents would enrich the wisdom of our esteemed readers. The present volume of journal is an outcome of the 4th “Kushagra International Management Conclave 2013” conducted in November 09, 2013 in collaboraton with University of Washington, Bothell, USA, supported by WASITRAC, USA & North Seattle Community College, USA. We sincerely acknowledge the valuable suggestion of Prof. J. B. Padhi, Secretary of KIIMS and guidance of the Board of Editors to bring this journal in our academic endeavour.
Chief Editor
Chief Patron
Editorial Advisors
Prof. J.B. Padhi Secretary, Kushagra Institute of Information & Management Science (KIIMS)
Prof. Samson Moharana Utkal University Bhubaneswar, India
Chief Editor
Prof. S. Krishnamurthy Director, School of Business University of Washington, Bothell, USA
Prof. S.K. Baral Director, Kushagra Institute of Information & Management Science (KIIMS)
Editorial Board
Prof. Marry Ellen O’Keeffe Vice President North Seattle Community College, USA
Prof. Malabika Deo Pondicherry University Puducherry, India
Prof. Keshav Raj Joshi Tribhuban University Kathmandu, Nepal
Prof. B.L. Mathur Rajastan University Jaipur, India
Prof. Chhanda Chakravorti Indian Institute of Technology Kharagpur, India
Prof. A.P. Pati North-Eastern Hill University Shillong, India
Prof. Sudipti Bannerjea Calcutta University Kolkata, India
Prof. B.P. Mishra Xavier Institute of Management Bhubaneswar, India
Contents 01.
02.
03.
04.
The Ability of the Aviation Industry to Bring Tourists and Development: The Case of Carbon Tax on Airlines to Achieve ''Green'' Outcomes Unathi Sonwabile Henama
01
Determination of Effective Financial Ratios for Identifying Default Risk for Small and Medium Enterprises (SMES): Reality vis-a-vis Bankers' Perception Muhammad Ziaulhaq Mamun
08
Entrepreneurial Performance in the Presence of Illegal Firm Activities and Constraining Investment Climate Syed Hasanuzzaman and Mohammad Shoyeb
17
Conceptualizing and Testing Advertising Demand Grid: A Prospective Tool for an Effective AD-Designing Brajesh Kumar and Gouranga Patra
27
05.
Non Fund Based Income in Indian Banking Sector: An Indepth Study Kishore Kumar Das
06.
Towards Identification of Variables that Constitute Corporate Citizenship Practices: Bangladesh Perspective A T M Mozaffor Hossain and Priyabrata Chowdhury
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64
07.
Globalisation: A Strategic Measure for Economic Regulation Prabir Chandra Padhy
72
08.
A Study on Performance of Public vs. Private Sector Life Insurance Companies in India Pinku Paul
79
09.
Financing Pattern and Utilisation of Fixed Assets: Case on Tata Steel and Sail Girija Nandini
91
10.
Foreign Investments in India: Potential & Performance of FDI Inflows with Special Reference to Sustainable Investment Renuka S Nifadkar and Anil P Dongre
11.
Openness—The Modern Mantra for Growth: A Study of Indian Economy (During 2000-2012) Biswajit Prasad Chhatoi and Deepak Pattanayak
12.
An Investigation into Role of E-Governance and its Implications in Education: A Reference to Higher Educational System Vijit Chaturvedi
99 114
132
13.
Foreign Investment in India in Post Globalization Era: Issues and Challenges Prabina Kumar Padhi and Madhusmita Mishra
143
14.
FMCG Protection in Volatile Times—An Analysis on Trend Setting Perspective P.K. Rath and S.K.Baral
151
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The Ability of the Aviation Industry to Bring Tourists and Development: The Case of Carbon Tax on Airlines to Achieve ''Green'' Outcomes Unathi Sonwabile Henama*
ABSTRACT The tourism industry is mostly labour intensive, employs a multiplicity of skills, allows the entry of locally owned small and medium enterprises and the tourism industry is an export product that earns foreign exchange par excellent. The tourism industry has a negative impact on the environment but on the other hand (Rigall-I-Torrent, 2007) by raising financial resources and the tourists' awareness of environmental value, tourism can increase the preservation of the environment. The tourism industry on the other hand has been identified by governments and legislators as an easy means of increasing the tax revenues of states, and governments. The aviation industry is a case in point which is being affected by increased taxation in addition to increased landing fees and the unstable price of crude oil for jet fuel. ''Aviation is indispensable for tourism, which is a major engine for economic growth, particularly in developing economies. Globally, 51% of international tourists travel by air'' ATAG (2012). In addition, the cost (Pearce, 2012) of air travel has fallen through the emergence of low cost carriers, and deregulation leading to greater competition. In order to ensure that the tourism industry yield more benefits, there has been a concerted push to ensure that tourists spend more money, stay longer and travel outside of the tourism beaten track. The aviation sector is crucial for the tourism industry to flourish because it leads to increased access for a destination area. According to Cornelissen (2005) the developmental advantages of tourism are not automatic there are some structural factors that eventually affect the economic impact of tourism, and transportation happens to be one of them. Technological innovations have ensured that new aircraft are more environmentally friendly than their predecessors. The introduction of carbon taxes on aviation is regrettable as the aviation industry has introduced measures to be more environmentally sensitive. Punitive carbon taxes as noted by Bisignani (2011) do nothing to reduce the aviation industry's negative environmental impact and actually deprive the aviation industry of needed financial resources through taxation. In addition, the aviation industry is over-taxed when compared to other means of transportation and does not receive subsidies from government. By increasing taxation, authorities are sacrificing the developmental impacts of the aviation industry. An overview of the current available research on carbon taxation in South Africa is embedded in this paper to indicate the advantages and potential negative impacts of carbon taxation. The paper is exploratory in nature and a review of literature was undertaken to add to the paucity of information about the into carbon taxation in South Africa. A variety of sources from journals, regulations and related institutional publications were used. Keywords: Tourism, Aviation, Mobility, Globalisation, Development etc.
INTRODUCTION ''Following the first racially inclusive democratic elections in 1994, the government efforts to eliminate poverty have been frustrated by the continued shedding of jobs from the formal economy'' Aliber (2003:473). In addition, Sparks (2007:3) noted that ''sub-Saharan Africa accounted for 2% of world trade in 2006...has the world's second most unequal distribution of income, after Latin America''. Poverty reduction is one of the goals of the Millennium Development Goals (MDGs). Economic growth is a necessary condition for poverty reduction according to Kadima (2007). However, economic growth is not a sufficient condition for poverty reduction, as concerted steps must be put in place to lift the poor out of poverty. The boom in the global economy has not strongly translated into decent new jobs: for every percentage point of global growth, formal sector employment has rise only by 0.3 percent according to the United Nations Development Programme Annual Report 2007 (2007). Bass et al. (2005) noted that the poor not only inadequate and unstable income, their lack material assets, *
Lecturer, Department of Tourism Management, Tshwane University of Technology, Pretoria, South Africa
The Ability of the Aviation Industry to Bring Tourists and Development: The Case of Carbon Tax
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and safety nets to mitigate and have little voice in political institutions to benefit their condition. The two most dominant economic sectors in South Africa namely agriculture and mining have been experiencing increased global competition, declining employment and increased mechanisation. South Africa is endowed with other natural resources such as platinum, diamonds, cobalt, gold and chromium. On the other hand South Africa has an energy intensive economy with a high reliance on fossil fuels largely due to an abundance of coal according to Moodley et al. (2005). As noted by Spacks (2007) the World Trade Organisation (WTO) change of trade policy in 2004 was the phasing-out of bilateral quotas on textiles and clothing resulting in India and China benefiting from this development due to their superior textiles industry. The effects of globalisation were increasingly being felt locally as job losses were as a result of increased competition from other countries. India and China benefited from lower input costs including labour. According to Sheeham (2008) South Africa's share of global manufacturing exports from 1999 to 2005 increased from a modest 0.35 percent to 0.43 percent which was below the global average in terms of export growth. Countries have been increasingly been looking for strategies and industries that would bring about development and growth. Services sector which are located in the tertiary level of economic activities has seen some of the highest growth in terms of contribution to GDP, and employment creation. Tourism is located in the services sector of the economy as an export product that is locally consumed and where all the value-adding occurs at the destination area. As noted by Hjalager (2007), the provision of tourism services cannot be outsourced from the destination area where they are produced, in an increasingly globalised world. The Reconstruction and Development Plan (RDP) adopted by the African National Congress (ANC) was not adopted by the market leading to the adoption of a SAP, the neoliberal Growth, Employment and Redistribution Strategy (GEAR) in 1996. It's therefore not a surprise that tourism became included in the country's economic development strategy with the promulgation of the White Paper on the Promotion and Development of Tourism in South Africa in 1996. At the centre of the SAPs was a need for the state to be minimalistic in the economy by only providing an enabling environment for growth and private investment. From the tourism cluster, the effect of GEAR was that South African Airways (SAA) was partially privatised and Aventura, the resort business of government was sold to a consortium including Kopano Ke Matla Investments (Congress of South African Trade Unions' investment Company). The tourism industry has been widely accepted as a means to ignite economic growth and development not only in developing nations but also in developed nations. Tourism is an export product in the services sector that is produced and consumed at the destination area. The fact that the tourism industry is labour intensive, employs a multiplicity of skills, allows the entry of locally owned small and medium enterprises and the tourism industry is an export product that earns foreign exchange par excellent. The tourism industry has a negative impact on the environment but on the other hand (Rigall-I-Torrent, 2007) by raising financial resources and the tourists' awareness of environmental value, tourism can increase the preservation of the environment.'' The environmental impacts of tourism are not simply those related to degradation caused by the volume of visitors, but the resource implications resulting from the operation of tourism-related businesses, such as transportation pressures, energy and water consumption, waste generation...the responsibility to protecting the resource base of tourism therefore rests with all tourism operators'' Hobson & Essex(2001:134). The Tourism White Paper (1996) had identified responsible tourism as the guiding principle of tourism development and growth in South Africa. The tourism industry on the other hand has been identified by governments and legislators as an easy means of increasing the tax revenues of states, and governments. TOURISM INDUSTRY IN SOUTH AFRICA South Africa is the first African country to have hosted a mega sporting event, the 2010 FIFA World Cup™ and the tournament increased the exposure and prestige of not just the continent but specifically South Africa.
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Tourism plays an increasing role in South Africa and tourism (WTTC, 2012) contributes 2.7% of total Gross Domestic Product (GDP) in 2011 and is forecasted to contribute 5.7% in 2012. Tourism is developed to create jobs, distribute income and benefit small, and medium businesses and South Africa is known for its unrivalled wildlife, wine, justice tourism and according to Cornelissen (2005) the Western Cape province of South Africa is one of the country's premier tourist attractions. South Africa has been to host to the World Summit on Sustainable Development (WSSD) in 2001 and several other major conferences, exhibitions and meetings. Tourism generates in excess of R48 billion in revenue from foreign tourists each year and since, 2000 has been growing volumes at rates averaging between 4% and 6% according to Airlift Strategy 2006 by the Department of Transport (2006). Van Schalkwyk (2012) noted that the tourism sustains one in 12 jobs globally and contributes 9% of worldwide gross domestic product. The tourism industry provides compelling reasons for its development in a country such as South Africa that has abundant wildlife, natural beauty and more than 2000 kilometers of coastline. The development and upgrading of supply-side infrastructure such as transportation will ensure that the benefit is for the dual benefit of locals and the tourists. Because tourism is an export product that is consumed in the tourism destination area, means of ''access'' to and from the destination are important to the success of the tourism destination. Burton (1995) advises that a tourist cannot make use of tourism resources unless they are accessible through a transport system of some sort that must link the tourist's home to their desired destination. The transport system consists of the following: *
The means of transport that includes cars, trains busses, aircraft; and
*
The network of routes upon which he means of transport travel such as roads, railway tracks, airports, and ports and is related as infrastructure.
''Commercial air travel commenced in the late 1920s, but, because of the cost and limited passenger carrying capacities, did not have much on an impact on tourism until later'' Inskeep (1991:8).However, according to Whitelegg (2003) aviation is predominantly a tourism industry and the tourism industry benefits from the liberalization of the aviation industry. The majority of South African use mini-bus taxis as a means of public transportation and the public transportation sector remains commuter-orientated. Transport infrastructure and transport operators form part of the important link of accessibility to the destination. Infrastructure has a catalystic role in growth and development of commerce and industry (Fedderke & Bogetic, 2005) by facilitating private investments by lowering production costs and opening up new markets, thereby creating new production, trade and profit opportunities. These in turn reduce transports costs, thereby reducing the cost of doing business and making firms more efficient, effective and competitive. The growth of tourism post World War II is attributed to the aviation advances due to military innovation that ensured that airlines where bigger, faster, and more safer. The construction of airport infrastructure ensured that these airports can be used, the absence of which may have seriously hampered access. The lack of road infrastructure means that the aviation industry can transports goods that are perishable over long distances. The lack of car-worthy road infrastructure in Africa can be mitigated by the aviation industry. Infrastructure must never be taken for granted as noted by Lohmann et al (2009) about the Dubai story where world class airlines and airports were set up to create a high reputation of service and attract particularly high yields passengers. Dubai was initially used by airlines as a hub and this allowed Dubai to develop its tourism industry with a focus on shopping from the benefits of the hub. In the United States according to a report by the Business Travel Coalition (2008) airlines are the primary source of intercity transportation and are critical to national and local economic development, the flow of human capital, the movement of just-in-time parts for manufacturing and the transport of perishable food and other goods upon which the economy depends. The transportation system and especially aviation has played an important role global mobility across the globe. There world has increasingly seen global mobility (Favell et al. , 2007) and Europe is the leader in terms of free The Ability of the Aviation Industry to Bring Tourists and Development: The Case of Carbon Tax...
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movement of people. Increasingly universities are seen as providers of highly skilled immigrant labour for their countries or from the migrants' perspective, as stepping stone to immigration. Cities that seek to benefit from globalisation by attracting more skilled personnel need to have investments in physical and infrastructure environments according Ewers (2007). In addition, there is low automobile access as noted by Behrens (2004) that in South Africa only 39% of middle-income have access to a car, whilst 50% of middle class were without private automobile access. Insurance costs are generally higher because of inherent risks such as hijacking, pirates and lawlessness on the continent. Aviation provides the only rapid worldwide transport network which makes it essential for global business and tourism (ATAG, 2012). TAXATION OF AVIATION According to Oxford (2011) airlines registered in South Africa carry 18 million passengers and 209,000 tonnes of freight a year to and from and within South Africa. ''Aviation is indispensable for tourism, which is a major engine for economic growth, particularly in developing economies. Globally, 51% of international tourists travel by air'' ATAG (2012). Aviation has a strong (Whitelegg, 2003) growth dynamic and is one of the few industries that can show growth rates of 7% per annum. Air transportation has been a major beneficiary of technological innovations stemming from research and developments into the military and aerospace industry. Air transport has experienced rapid expansion since the Second World War as the global economy has grown and the technology of air transport has developed to its present state (Commission on Sustainable Development, 2001). The tourism industry has been specifically used by many countries, developed and developing to acts as a catalyst for growth and development. According to the Commission on Sustainable Development (2001) demand for air freight service is also primarily a function of economic growth and international trade. According to an a document titled The Economic Impact of Air Service Liberalisation by InterVISTAS (2007) traffic growth subsequent to liberalization of air services agreements between countries typically averaged between 12% and 35%, significantly greater during years preceding liberalization. Landlocked counties and small island countries can have aviation as an alternative to the high transport costs over land. This is confirmed by AU (2009) that landlocked developing countries pay almost four times more for transport services than developed countries, the transport costs for landlocked African countries can be as high as 77 percent of the value of exports.
The tourism industry and aviation have to respond to challenges that are faced by the environment. The transport sector is also a major polluter whilst (Friends of the Earth, 2005) aviation is the fastest growing contributor to climate change. ''Despite its many advantages, air transport is associated with significant impact on the environment, mainly due to its emissions which in turn lead to air pollution, ozone layer depletion, and global warming. The noise from aircrafts, particularly during take-off and landing, is also a source of negative impact on human health'' according to Commission for Africa (2009:60). Currently, the global emissions from international aviation transport account for about 1% of total anthropogenic CO2 emissions. As noted by Van Schalkwyk (2012:2) '' slowing down aviation and tourism growth to reduce carbon emission will be in no-one's interest. It will destroy jobs and undermine our efforts to reduce poverty''. The South African Treasury has announced the introduction of a nation-wide carbon tax as part of the 2012 budget. South Africa wants to reduce greenhouse gas emissions (GHG) and according to National Treasury (2010) South Africa has voluntarily announced to reduce domestic GHG emissions by 34 per cent by 2020 and 42 per cent by 20205. The rational for the tax is to mitigate climate change by pricing carbon dioxide emissions so that the costs associated with such emissions are incorporated into production costs and consumer prices according to the South African Revenue Service (2012). Apparently the introduction of the taxation would lead to change of behaviour through the uptake of more energy-efficient technologies. This prompted the IATA Director General to lobby the
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Minister of Transport to reconsider the issue of carbon tax as this will have a detrimental effects on aviation as this carbon tax will deprive the industry of the financial resources to invest in emission reducing measures (Bisignani, 2011). As noted by Button (2005) the air transportation industry, generally seen as a luxury good is a convenient subject for taxation and the collection of such taxes is convenient and inexpensive. This is not the case as the cost of air travel has lowered with LCCs, increased competition and greater connectivity. Because of greater private sector ownership in the aviation sector as opposed to public transport such as rail and buses, public transportation can benefit from state subsidies for fares, operational costs and infrastructure. Aviation pays for all its infrastructure costs, and more, through taxes and user charges making a net contribution to public funds according to ATAG (2004). Taxation is usually though to discourage the use of something, like alcohol or cigarette, in the case of aviation, it may actually lead to increased transportation costs and the price elasticity of tourism demand may mean lower tourists visiting a destination. Taxation has the potential of destroying progress in aviation as opposed to advancing the sustainability and growth of the aviation sector. The general increase of aviation tax has a detrimental impact on travel for business and increases the cost burden to tourists. In other words, aviation taxation does more harm than good, as the benefits foregone far outweigh the benefits accrued from taxation. Therefore, there is a greater economic cost for taxation of the aviation industry, not just for the aviation but also the wider economy. Taxation therefore discourages efficiency and productivity by heavily taxing the industry that creates those conditions. The Minister of Tourism has been also critical of the high landing fees in South Africa which puts them as one of the highest in the world. This results in aviation being one of the most taxed sectors of the economy. In addition to aviation taxes, landing fees going up can distort aviation demand by driving up costs, acting a form of taxation. Government have the legislative rights to tax any industry but the aviation industry is being singled out time and time again. These increases in taxes are passed on to airline passengers as they increasingly become price sensitive. From a customer perspective this can lead to mode of transportation switching which can lead to the use of less efficient and effective transportation which may be less expensive and less efficient in terms of speed. From the perspective of the legislators, the reduction of greenhouse gas (GHS) (Winkler & Marquard, 2011) through a carbon tax would have a demand effect by reducing demand for energy due to high price and substitution effect, from more to less carbon intensive fuels due to high energy costs. The demand effect will fail as demand for aviation is to increase in the presence of increasing taxing, but the taxation would limit the economic benefit from aviation. This will also limit the jobs that the aviation industry creates directly and indirectly and according to Oxford (2011) airlines contribute nearly R23.5 million to the economy and support 89,000 jobs in South Africa. Benefits of aviation are not such economic; they are also social according to FDA (2011) the role of air travel evolves into an integral part of our lives connecting friends, relatives and commercial opportunities. In addition, according to ATAG (2004) air transport not only provides access to remote areas for social inclusion it also facilitates the delivery of emergency and humanitarian aid relief. The increase in aviation would most certainly reduce funds that could further strengthen the programmes of aviation to be more environmentally friendly. Increased taxation would (ATAG,2004) reduce funds available for research programmes that aim to achieve a further 50% fuel saving and an 80% reduction in oxides of nitrogen by 2020. The taxation will not lead to lower pollution but higher aviation will lead to less aviation transportation limiting the developmental potential of aviation. As noted by Sharpley (2004) sustainable development in the tourism industry has been based on the preservation of the natural, built and socio-cultural resource base upon which tourism depends for the long-term survival of tourism.
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CONCLUSION The pro-active steps taken by South Africa to mitigate greenhouse gas emissions considering that (Alton et al., 2012) South Africa is amongst the world's most carbon intensive economies. The tourism industry and aviation would continue to produce negative environmental impacts, is an almost certainty. The aviation industry has already started to make inroads in trying to minimise its impact on the environment by reducing the noise levels, more fuel efficient aircraft and reducing the carbon print even in the aviation value chain. What is undeniable is the value that aviation has on the economic growth, economic efficiency and connectivity it provides to destinations. The unfair taxation of the aviation sector relative to other transport modes is unfair as this limits the developmental potential of aviation. Carbon taxes take away the resources that could be utilised to achieve green outcomes by the aviation sector. The taxation is problematic considering there is lack of a uniform taxation system for aviation in as much as this is discouraged. As noted by Hobson & Essex (2001) the response of the tourism industry to the concept of sustainable development has been mixed. The problem with tourism is that it started a development path that depleted the natural resource base, with foreign owned companies that resulted in high levels of leakage from the local economy resembling the core-and-periphery theory in developmental economics. The profits would be produced at the periphery and be repatriated to the centre, with little benefits and all the environmental degradation at the peripheral area.
Local ownership of the aviation industry to achieve sustainable development is impossible and as noted by Sharpley (2004) that sustainability can be a barrier to the development of tourism as it limit the number of tourism and restrict business opportunities. The aviation industry with the mass movement of people that it provides across the world has all the hallmarks of mass tourism. The rhetoric about the negative impact reduces of aviation (and specifically mass tourism) reduces the positive impact that it makes to the economic development, growth and providing the resources to mitigate the negative environmental impacts. ATAG (2003) had noted that the Europe accounts for 41% of total international arrivals to Africa and the majority are transported by air. Because of the developmental challenges facing many African countries, and poor infrastructure, the aviation industry is still a small player in terms of contributing to GDP. However, the little contribution that aviation makes in absolute terms are impressive with the scope that the aviation sectors contribution to GDP will increase in the future. Taxing aviation is taxing economic growth and development, its taxing progress, its taxing the reduction in transport costs. The aviation industry must be allowed to be creative in providing solutions to the its negative environmental impacts as airports have already out in additional restrictions of the carbon footprint of airlines. Carbon taxation would destroy that the aviation creates directly and indirectly and this means that carbon taxation would achieve the direct opposite objective of reducing emissions simultaneously with economic growth and development. As noted by the Department of Minerals and Energy (DME) energy efficiency is a key to enhance the clean energy development and to mitigate the negative environmental effects of energy on humans and the environment. The aviation industry has already used implemented energy management programs and further taxation would be punitive to the economic benefits of the industry on the economy and a social cost to humans. REFERENCES 01.
Abeyratne, R.I.R. (1998). The future of African civil aviation. Journal of Air Transportation World Wide, 3(2):30-49.
02.
African Union. (2009). The AU/NEPAD African Action Plan 2010-2015: Advancing Regional and Continental Integration in Africa.
03.
Aliber, M. (2003). Chronic Poverty in South Africa: Incidence, Causes and Policies. World Development, 31(3):473-490.
04.
Altman, M. (2006). Identifying employment-creating sectors in South Africa: The role of service industries. Development Southern Africa, 23 (5):627-647.
05.
Air Transport Action Group. (2003). The contribution of air transport to sustainable development in Africa. Retrieved from: http://www.atag.org. [Accessed 01 March 2012].
06.
Alton, T., Arndt, C., Davies, R., Hartley, F., Makelov, K., Thurlow, J. & Ubogu, D. (2012). The economic implications of introducing carbon taxes in South Africa. World Institute for Development Economic Research, 46:1-22.
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07.
Air Transport Action Group. (2004). The economic & social benefits of air transport. Retrieved from: http:// www.atag.org. [Accessed 01 March 2012].
08.
Behrens, R. (2004). Understanding Travel Needs of the Poor: Towards Improved Travel Analysis Practices in South Africa. Transport Reviews, 24(3):317-336.
09.
Bisignani, G. (2011). South African Carbon Tax: Letter from the Director General & CEO of IATA to the Minister of Transport of South Africa, Mr. J.S. Ndebele. Montreat: IATA.
10.
Cornelissen, S.(2007). Tourism impact, distribution and development: The spatial structure of tourism in the Western Cape province of South Africa. Development Southern Africa, 22 (2): 163-185.
11.
Department of Education. (2008). Human Resources Development Strategy for South Africa. Pretoria: DoE.
12.
Department of Environmental Affairs and Tourism. (1996). White Paper on the Promotion and Development of Tourism in South Africa. Pretoria: DEAT.
13.
Department of Environmental Affairs & Tourism. (2005). 2010 Soccer World Cup Tourism Organising Plan: Executive Summary. Pretoria: DEAT.
14.
Department of Mineral and Energy. (2004). Draft energy efficiency strategy of the Republic of South Africa. Pretoria: DME.
15.
Fedderke, J.W. & Bogetic, Z. (2005). Infrastructure and Growth in South Africa: Direct and Indirect Productivity Impacts of 19 Infrastructure Measures. Cape Town: University of Cape Town.
16.
Economic Commission for Africa. (2009). Africa Review Report on Transport. Sixth Session of the Committee on Food Security and Sustainable Development (CFSSD-6) Regional Implementation Meeting (RIM) for CSD-18. Retrieved from: http://www.un.org. [Accessed 01 March 2012].
17.
Federal Aviation Administration. (2011). The Economic Impact of Civil Aviation on the U.S. Economy. US Department of Transportation. Source Unknown.
18.
Hjalager, A.M. (2007). Stages in the economic globalisation of tourism. Annals of Tourism Research, 24(2): 437-457.
19.
Hobson, K. & Essex, S. (2001). Sustainable tourism: A view from accommodation businesses. The Service Industries Journal, 21 (4): 133-146.
20.
Inskeep, E. (1991). Tourism Planning: An Integrated and Sustainable Development Approach. New York: John Wiley & Sons.
21.
Lowitt, S. (2006). Foreign tourism's contribution towards growth and job creation in South Africa. Pretoria: HSRC.
22.
National Treasury. (2010). Reducing greenhouse gas emissions: Discussion paper for public comment. Pretoria: National Treasury.
23.
Pearce, B. (2012). The state of air transport markets and the airline industry after the great recession. Journal of Air Transport Management, 21:3-9.
24.
Rigall-I-Torrent, R. (2007). Sustainable development in tourism municipalities: The role of public goods. Tourism Management, 10(4):1-15.
25.
Sharpley, R. (2004). Sustainability: A Barrier to Tourism Development? In. Sharpley, R & Telfer, D.J. Tourism and Development: Concepts and Issues. Clevedon: Channel View Publications.
26.
Telfer, D.J. (2004). The evolution of tourism and development theory. In. Sharpley, R & Telfer, D.J. Tourism and Development: Concepts and Issues. Clevedon: Channel View Publications.
27.
Van Schalkwyk, M.(2012). Address by the Minister of Tourism, at the air transport action group aviation and environmental summit, Geneva (21/03/2012). Retrieved from: http://www.polity.org.za/article. [Accessed 01 March 2012].
28.
Whitelegg, J. (2003). The Economics of Aviation: A North West England Perspective. Source Unknown.
29.
World Travel and Tourism Council. (2012). Travel and Tourism Economic Impact 2012: South Africa. London: WTTC.
30.
Winkler, H. & Marquard, A. (2011). Analysis of the economic implications of a carbon tax. Journal of Energy in Southern Africa, 22 (1): 55-68.
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Determination of Effective Financial Ratios for Identifying Default Risk for Small and Medium Enterprises (SMES): Reality vis-a-vis Bankers' Perception Dr. Muhammad Ziaulhaq Mamun*
ABSTRACT Bangladesh suffers from deficiencies in its existing banking system that prevents the appropriate catering of financial needs of the SMEs. Based on the assessment of financial measures of sample SMEs, this paper identified five long-term measures like, operating profit margin ratio, interest coverage ratio, payables turnover ratio, return on assets ratio, and asset coverage ratio as the most predictive variable ratios for identifying SME's chances of default. However, in reality, the Relationship Managers1 emphasize on short-term measures like, quick ratio, acid test ratio, operating cash flow ratio and fixed charge coverage ratio for identifying the default cases. Thus the gap in the perception of the managers and the reality puts into focus the obvious lack of structure in the risk assessment system of SME banking. The findings from this analysis of emphasizing long-term measures can be used with information from basic balance sheets and income statements available to each Relationship Managers in the SME departments of Banks. Keywords: Patent, Banker, Industry, Risk, SMEs etc.
INTRODUCTION The growing economic significance of SMEs as sources of new business creation and employment generation in the developed, OECD countries, especially since 1970s, is now widely recognized in an increasingly growing volume of literature (OECD 1997). SMEs are undoubtedly quite predominant in the industrial structure of Bangladesh, and comprise over 90% of all industrial units (Ahmed 2001). Together, the various categories of SMEs are reported to have contributed between 80 to 85% of Bangladesh's industrial employment and 23% of the total civilian employment in Bangladesh (SEDF 2003). In addition SMEs of Bangladesh share nearly 35% of the gross output of the entire manufacturing sector (Table 1).
Table 1: Contribution of Large and Small Industries to GDP (%) Industry 1999-00
2000-01
2001-02
2002-03
20 03- 04
20 04- 05
20 05- 06
Large
11.01
11.13
11.16
11.29
11.47
11.66
12.14
Small
4.39
4.46
4.60
4.68
4.78
4.85
4.94
Total
15.40
15.59
15.76
15.97
16.25
16.51
17.08
20 07 -8
20 08- 09
20 09- 10
20 10- 11
Industry 20 06- 07 Large
12.47
12.63
12.71
12.68
13.12
Small
5.08
5.14
5.18
5.26
5.29
Total
17.55
17.77
17.90
17.94
18.41
Source: Economic Review, Ministry of Finance, Government of Bangladesh, 2012.
*
Professor, Institute of Business Administration (IBA), University of Dhaka, Bangladesh
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Kushagra International Management Review
LITERATURE REVIEW Despite high dependence on the agricultural sector, other sectors are growing significantly in Bangladesh. Over the years, the share of agriculture in GDP is declining with the services and manufacturing sectors rising as the driver of growth in the country. The manufacturing sector in Bangladesh has been contributing at a consistent rate of around 15% over the last decade. A nationwide survey claims that Micro, Small and Medium Enterprises (MSMEs) account for a value addition of 20-25% to Bangladesh's GDP (Daniels 2003). These MSMEs are currently accommodating the employment of more than 30 million people of the country aged 15 years and above (BBS, 2010). Table 2 shows the contribution of SMEs with different worker groups in the GDP on Bangladesh (BBS 2010).
Table 2: Contribution of SMEs in the GDP on Bangladesh Range of Number of Workers of the SMEs
Total Contribution to GDP (Tk2)
Percentage of Total Contribution (%)
0-1
193 996 555 714
26
2-5
379 663 897 358
51
6-10
73 120 983 681
10
11-20
45 183 240 157
6
21-50
33 960 498 076
5
51-100
15 138 922 373
2
Total
741 064 097 360
100
Source: BBS (2010), Note: US $ 1 = Tk. 70.00 The availability of fund for SME financing in Bangladesh is a major constraint obstructing the formation and growth of SMEs in Bangladesh (Mintoo, 2006). Banks are reluctant to expand their SME credit portfolio because SME lending is not an attractive and profitable undertaking for them. SMEs are regarded as high risk borrowers by bank officials because of their low capitalization, insufficient asset base, inability to comply with collateral requirements and high mortality rates and consequently, they are not offered any attractive deals in terms of loans and interest rates (Sia, 2006). SAPRI (1999) SME survey conducted on 500 SMEs in Bangladesh (with the inclusion of RMG, leather and agro-based SMEs) revealed several demand side (borrowers' perception) and supply side (bankers' perception) barriers that hinder the growth and development of SMEs in Bangladesh. On the demand side, the report noted that 79.4% of SME borrowers face collateral problems in obtaining credits from different commercial banks. The second most problem they face is bribery (66%), which increases their cost of funds. SMEs also face problems like delay in getting loans (54.6%), high interest rates (39.2%) disinterest from the part of banks (27.8%), requirement of guarantees (27.80%) and harassment (11.3%). The SAPRI report also mentioned that 55% of the borrowers had to visit the bank 8-15 times, while 20% were required to visit 16-30 times, in contrast with one time for the case of money lenders and friends, in order to get funds. This entire situation, in fact, has increased the cost of funds in doing businesses and has created frustration in the minds of the entrepreneurs of the SMEs. On the supply side barriers, the report mentions various factors such as the requirement of collateral, equity margin, high transaction costs, shortage of skilled manpower, high risk premium, lack of profitability, lack of standard product, and lack of market access that prevent banks from disbursing credit to SMEs and start-ups. In almost every part of the world, limited access to finance is considered a key constraint to private sector growth. Despite the fact that small and medium enterprises constitute a vital sector of the economy of Bangladesh in terms of creation of industrial output and generation of employment, they face a severe crisis of capital for their growth and development. A most recent private enterprise survey reveals that 58% of the SMEs in Bangladesh
Determination of Effective Financial Ratios for Identifying Default Risk for Small and Medium...
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suffer from a lack of investment funds and 35% of them suffer from a lack of operating funds (Daniels 2003). SMEs involved in the export sector also have the problem of accessing working capital and there currently exists no credit insurance policy for them. Credit availability is constrained for SMEs, being limited to certain forms of secured credit, along with family and informal credit. Formal credit comes with very difficult terms for SMEs, since banks do not maintain a proper portfolio for SMEs that determines the entity's creditworthiness separately from large corporates. In Bangladesh, there is a lack of coordinated evaluation for Small and Medium sized enterprises. According to preliminary interviews of the SME experts, there is a blatant need for quantitative, convenient and predictive measures on SME default. In the current context, the Relationship Managers (RM) of individual banks spends weeks examining the prospective clients' account books to see sales trends and understand the potential of the clients' businesses. The RMs have to form the balance sheets and income statements for the Small firms. Further they have to analyse already formed reports for the medium firms. As bankers are not aware of any model that predicts the chances of a SME defaulting in their loans, they are unable to grant proper financing to these firms without sacrificing their vested interests for the profit of banks. These situations have created an interest among bankers of the country in identifying predictors that can assess default risk of SMEs and create a model for banks that will allow them to cater to SMEs' financing and non-financing needs. OBJECTIVES The main objective of this research paper is to identify the most predictive financial ratios for the entities' probability of default extracted from their financial statements. Specifically, the paper analyzed a complete set of financial ratios linked to SMEs in Bangladesh, investigated the gap that exists between the perceptions of bankers against the reality of predictive financial measures that effectively model SME default risk, suggested a distinct model for predicting SME default that can be adopted by banks to benefit both parties and help stimulate further economic growth in Bangladesh. METHODOLOGY The research consists of both primary and secondary data and pertinent literature review. The coverage of SMEs as defined by the Industrial Policy is very broad - capturing business enterprises with a fixed capital ranging from Tk. 1 million to 300 million and employment between 10 - 99 people (GOB 2010). Given the time and resources limitation and accessibility and convenience, SMEs and bankers were chosen from i) SMEs operating in Dhaka, the capital of Bangladesh and ii) bankers in SME Departments of commercial banks of Bangladesh. The research surveyed 30 SMEs' data from their yearly financial statements over a period of five years (2003 - 2007) that resulted into 155 records. In addition 70 bank officials from SME departments of 16 banks at Dhaka were also interviewed.
For the purpose of this study, non-probability convenience sampling was employed. In few cases judgment was used for sample selection. Specifically expert sampling was used for surveying bank officials, with known or demonstrable experience and expertise in this area. They were asked to examine and comment on the appropriateness and validity of financial ratios that were chosen. This study make use of various statistical tools like mean index analysis, factor analysis3, binary logistic regression4, etc., using Microsoft Excel and SPSS software for data analysis. Due to restrictions in terms of resources, this research is limited to surveying 30 SMEs and 70 bankers in SME departments of banks operating in Dhaka. SMEs surveyed may not portray accurate and current information about their financial performances or other parameters as the SMEs were reluctant to provide current information. So this paper assesses the set of financial ratios based on data from years 2003 - 2007, as agreed upon and supplemented by the SMEs. Other limitations include:
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Data collected from the financial statements cannot be further verified. In several cases, the default of the borrowers might be due to internal factors of the bank or the company unrelated to the financials which couldn't be investigated for this paper. Kushagra International Management Review
In case of probability of default, there can be other causal factors like industry-related issues which have been avoided for simplicity of the analysis. The cooperation of banks concerning information about their lending policies and actual number of SMEs served cannot be verified.
VARIABLE ANALYSIS The expert opinion and a preliminary data analysis regarding the financial information from SMEs identified 19 relevant financial ratios (indicators of loan default of a firm) under five categories: i) Profitability, ii) Liquidity, iii) Leverage, iv) Coverage and v) Activity (Table 3). These ratios are considered as independent variables. The dependent variable is the loan default of SMEs. This is a bi-variate nominal variable with two outcomes (Yes and No). Next the financial ratios and the loan default rate of SMEs are analyzed from different angles.
Table 3: Financial Ratios and Corresponding Variables Parameters Profitability Ratios
Financial Ratios Operating Profit Margin Ratio Return on Assets Cash Return on Assets Return on Investment
Liquidity Ratios
Current Ratio Quick Ratio Cash Ratio Net Working Capital Ratio
Leverage Ratios
Debt-Equity Ratio Debt Ratio Degree of Operating Leverage
Coverage Ratios
Interest Coverage Ratio Net Gearing Ratio Asset Coverage Ratio Debt Coverage Ratio
Activity Ratios
Asset Turnover Ratio Inventory Turnover Ratio Receivables Turnover Ratio Payables Turnover Ratio
FINDINGS AND ANALYSIS
Binary Logistic Regression for All Variable Ratios A binary logistic regression analysis was conducted, pair-wise (loan default as dependent variable and a financial ratio as explanatory variable), to predict the default risk of SMEs using all the 19 ratios (Table 4). The results noted that only five ratios has shown significant relationship (at ? = 5%) with the default risk of SMEs indicating that these predictor ratios reliably distinguished the default and non-default cases of SMEs. These are i) Operating Profit Margin Ratio, ii) Interest Coverage Ratio, iii) Payables Turnover Ratio, iv) Return on Assets and v) Asset Coverage Ratio. As noted these are mainly profitability, coverage and activity ratios. These also indicate the fundamental business health and long-term sustainability of the firms. The test results based on Nagelkerke's R Square show that only Operating Profit Margin Ratio has strong correlation (r=0.44) and the rest of the rations has moderate relationship (0.33? r ?0.25) between the predictor and Determination of Effective Financial Ratios for Identifying Default Risk for Small and Medium...
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the prediction. Overall prediction success was found to be above 94.8% for these 5 ratios. The comparatively high values of Wald criteria demonstrated that these ratios made significant contribution to prediction. Comparatively low values of EXP (B)/ (i.e., negative B) values indicated that increasing values of the ratios will correspond to increasing odds of the default's occurrence. Therefore, it can be concluded that the five ratios are significantly correlated to default. Table 4: Summary of Binary Logistic Regression Results for Different Ratios Variable
P-Value (Model/Ratio)
Correlation Coefficient
Prediction Success
WALD/ EXP (B)
1.
Operating Profit Margin Ratio 0.001/0.003
0.4405
95.5%
8.856/0.025
2.
Interest Coverage Ratio
0.015/0.030
0.3332
94.8%
4.719/0.887
3.
Payables Turnover Ratio
0.029/0.021
0.3000
94.8%
0.984/0.498
4.
Return on Assets
0.041/0.043
0.2811
94.8%
4.104/0.063
5.
Asset Coverage Ratio
0.074/0.046
0.2470
94.8%
2.476/0.12
6.
Inventory Turnover Ratio
0.108/0.178
0.2236
94.7%
1.812/0.616
7.
Cash Ratio
0.228/0.300
0.1673
94.8%
1.073/0.591
8.
Asset Turnover Ratio
0.323/0.333
0.1378
94.8%
0.937/0.464
9.
Net Working Capital Ratio
0.315/0.326
0.1378
94.8%
0.964/0.209
10.
Degree of Operating Leverage
0.398/0.336
0.1225
93.5%
0.927/1.173
11.
Debt Coverage Ratio
0.424/0.486
0.1095
94.8%
0.485/0.767
12.
Receivables Turnover Ratio
0.658/0.646
0.0632
94.8%
0.211/1.002
13.
Net Gearing Ratio
0.776/0.816
0.0447
94.8%
0.054/0.988
14.
Cash Return on Assets
0.810/0.812
0.0316
94.8%
0.057/0.568
15.
Debt-Equity Ratio
0.8060.832
0.0316
94.8%
0.045/0.976
16.
Return on Investment
0.869/0.876
0.0316
94.8%
0.024/0.978
17.
Quick Ratio
0.989/0.989
0.0000
94.8%
0.000/1.002
18.
Current Ratio
0.889/0.887
0.0000
94.8%
0.020/1.019
19.
Debt Ratio
0.090/0.900
0.0000
94.8%
0.016/1.211
Bankers' Perception Regarding the Predictability of Default The survey data on the responses (in a scale of 1-10, where 1: least trusted, 10: most trusted) of 70 bankers regarding a picture of the ratios that the bankers trusted or would incline to in terms of predicting fault are summarized in table 5. The mean indices of the variable ratios indicated that quick ratio (8.89), acid test ratio (8.89), operating cash flow ratio (8.66) and fixed charge coverage ratio (8.66) are the variables emphasized the most by the respondents. Next in the list are current ratio (7.57), interest coverage ratio (7.56), debt service coverage ratio (7.47), and return on assets ratio (7.36). On the other extreme return on invested capital (1.94), degree of combined leverage (2.50), inventory turnover ratio (3.00), asset turnover ratio (3.31) are the least emphasized variables in terms of predicting fault. Hence it can be concluded that the bankers emphasize liquidity ratios mainly for identifying defaults. These in fact focus short-term health of the firms and are not true predictors of credit default. 20
Kushagra International Management Review
Table 5: Descriptive of Bankers' Perception Score to Ratios Variable
N
Minimum Maximum Mean Index
Std. Deviation
1.
Quick ratio
70
8
10
8.89
0.826
2.
Acid test ratio
70
8
10
8.89
0.826
3.
Operating cash flow ratio
70
7
10
8.66
1.089
4.
Fixed charge coverage
70
7
10
8.66
1.089
5.
Current ratio
70
6
9
7.57
1.015
6.
Interest coverage ratio
70
6
9
7.56
1.099
7.
Debt service coverage ratio
70
4
9
7.47
1.201
8.
Return on assets ratio
70
6
9
7.36
1.143
9.
Payable turnover ratio
70
4
8
6.06
1.295
10.
Interest coverage ratio
70
4
8
5.56
1.072
11.
Return on equity ratio
70
4
8
5.54
1.125
12.
Cash return on assets ratio
70
2
8
5.43
1.258
13.
Debt/equity ratio
70
1
8
5.34
1.433
14.
Asset coverage ratio
70
3
6
4.87
1.128
15.
Debt ratio
70
3
6
4.66
1.089
16.
Receivables turnover ratio
70
2
6
4.26
1.099
17.
Asset turnover ratio
70
1
5
3.31
1.222
18.
Inventory turnover ratio
70
1
5
3.00
1.330
19.
Degree of combined leverage
70
1
4
2.50
1.164
20.
Return on invested capital
70
1
3
1.94
0.832
Gap between Banker's Perception and Actual Predictive Ability The blatant difference between the banker's perception and the actual predictive ability of the ratios, as noted above, shows the actual misinformed nature the Relationship Managers work under. As the research identified that where the Relationship Managers mainly emphasize on liquidity ratios (e.g., on Quick Ratio, Acid Test Ratio, Operating Cash Flow Ratio and Fixed Charge Coverage Ratio) for identifying defaults the actual predictive ability mainly depends on profitability, coverage and activity ratios (e.g., Operating Profit Margin Ratio, Interest Coverage Ratio, Payables Turnover Ratio, Return on Assets Ratio and Asset Coverage Ratio). The disparity uncovers a need for a revision of evaluative emphasis of the criteria Relationship Managers use in banks. DIMENSION REDUCTION THROUGH FACTOR ANALYSIS
A Principal Factor Analysis with orthogonal rotation4 (Varimax) using the SPSS statistical package was performed on the survey data and was used to group the ratios to limited number of factors5. The factor analysis of 19 variables with 155 sample is found adequate (KMO test result = 0.627 ? 0.5) and valid (Bartlett's test of sphericity indicates a significance level of 0.000). The analysis has reduced the 19 ratios to 5 factors which explain 80.025% of the variability. The communalities6 of the variables that constituted the factors are found very strong, which indicates strong relationships among the variables (Appendix 1).These factors and corresponding variables are as follows: Determination of Effective Financial Ratios for Identifying Default Risk for Small and Medium...
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(1)
Factor 1: Return on Assets, Asset Coverage, Interest Coverage Ratio, Operating Profit Margin Ratio, Debt Coverage Ratio, and Asset Turnover Ratio
(2)
Factor 2: Cash Ratio, Cash Return on Assets, Receivables Turnover Ratio, Quick Test Ratio, Net Working Capital Ratio, and Current Ratio
(3)
Factor 3: Payables Turnover Ratio, Inventory Turnover Ratio, Debt Ratio
(4)
Factor 4: Debt Equity Ratio, Net Gearing Ratio, Return on Investment
(5)
Factor 5: Degree of Operating Leverage
As can be noted that factor 1, which explains 38.017% of the variability, includes four out of five variables (Return on Assets, Asset Coverage, Interest Coverage Ratio, and Operating Profit Margin Ratio, except Payables Turnover Ratio) that has shown significant relationship (at ? = 5%) with the default risk of SMEs indicating that the predictor reliably distinguished the default and non-default of SMEs. This supports our previous findings of significant relationship of the five ratios with default risk of SMEs. It is also noted that, all the variables of factor 1 have high factor loadings7 (above 0.6). This clearly shows the relative strengths of these individual ratios (Appendix 2). Further a binary logistic regression analysis was conducted individually to predict the default risk of SMEs using the five new factors as predictor. Only factor 1 has shown significant relationship at ?=10.3%. The test results based on Nagelkerke's R Square show that factor 1 has a moderate correlation (r = 0.24) with the default risk (WALD 2.32, EXP B = 0.49). Other factors has shown insignificant relationship (level of significance is 0.975, 0.32, 0.862, and 0.409 for factor 2, 3, 4 and 5 respectively) with default risk of SMEs. RECOMMENDATION AND CONCLUSION SMEs in Bangladesh account for 25% of the country's GDP, 80% of industrial jobs, and 23% of the total labor force. Despite the fundamental roles played by SMEs in developing the country's economy through stimulating large scale employment, investment, development of indigenous skill and technology, promotion of entrepreneurship and innovativeness, and enhancement of exports; Bangladesh suffers from deficiencies in its existing banking system that prevents the appropriate catering of financial needs of these enterprises. Based on the assessment of financial measures of a sample of 30 SMEs over a period of five financial years, this paper determines the set of financial ratios that are most predictive of an SME's chances of default. Based on field questionnaires distributed to 70 SME bankers, the paper additionally outlines the differences between perception of bankers and the reality of the financial ratio sets that act as predictors to the entities' default risk.
Regression, factor analysis, and mean score were used to determine the relationship between the default risk and individual financial ratios. A total of nineteen ratios were used as independent variables and the default and non-default attributes of the SMEs were used as dependent variables. Five ratios are found highly accurate in predicting default risk are operating profit margin ratio, interest coverage ratio, payables turnover ratio, return on assets ratio, and asset coverage ratio. As noted these ratios measure fundamental business health and long-term sustainability of a firm. This is supported through factor analysis. However the Relationship Managers emphasis was on short-term measures like Quick Ratio, Acid Test Ratio, Operating Cash Flow Ratio and Fixed Charge Coverage Ratio. The gap in the perception of the managers and the reality puts into focus the obvious lack of structure in the risk assessment system of SME banking. Thus the findings from this analysis of emphasizing more on long-term business health measures rather than current focus of short-term measures can be utilized with information from basic balance sheets and income statements available to each Relationship Managers in the SME departments of Banks. Accordingly the problems in the current banking scenario can be adequately addressed by the analysis in this research. 22
Kushagra International Management Review
NOTES 1 Relationship Managers (RM) are responsible for financial analysis of the credit worthiness of the SMEs.
2
Tk, the abbreviation of Taka, the currency of Bangladesh. $1 = Tk. 70.
3
Factor Analysis is a type of analysis used to discern the underlying dimensions or regularity in phenomenon. It general purpose is to summarize the information contained in a large number of variables into a smaller number of factors. It is an interdependence technique in which all variables are simultaneously considered.
4
The rationale for using the statistical tool, binary logistic regression, is that one of the variables, i.e., loan default, has just two outcomes (yes or no). Hence a conventional correlation analysis is inapplicable here. The binary logistic regression determines the accuracy to which the financial ratios are able to predict loan default. The binary logistic regression gives a list of relevant ratios that predict loan default with a high level of accuracy.
5
Orthogonal refers to the mathematical independence of factor axes to each others (i.e., at right angles, or 90 degrees). Factor rotation is the process of manipulating or adjusting the factor axes to achieve a simpler and pragmatically more meaningful factor solution.
6
Factor is a linear combination of the original variables. Factors also represent the underlying dimensions (constructs) that summarize or account for the original set of observed variables.
7
Communality refers to a measure of the percentage of a variable's variation that is explained by the factors. It is the amount of variance an original variable share with all other variables included in the analysis. A relatively higher communality indicates that a variable has much in common with the other variables taken as a group.
8
'Factor loading' is a measure of the importance of the variable in measuring each factor. It is used for interpreting and labeling a factor. It is the correlation between the original variables and the factors, and key to understanding the nature of a particular factor.
REFERENCES 1.
Ahmed, Momtaz Uddin (2001). Globalization and Competitiveness of Bangladesh's Small-scale Industries ( SSIs): An Analysis of the Prospects and Challenges, in CPD/UPL published, Bangladesh facing the Challenges of Globalization, IRBD, 2001.
2.
BBS (2010). Statistical year Book 2010, Bangladesh Bureau of Statistics, Ministry of Planning, Government of Bangladesh.
3.
Daniels, Lisa (2003). Report on the National Private Sector Survey of Enterprises in Bangladesh, International Consulting Group, Melbourne, Australia, Web: http:// adb.org/ Documents/ RRPs/ BAN/ rrp-ban-35225.pdf
4.
GOB (2004). Economic Review, Ministry of Finance, Government of Bangladesh, 2010.
5.
GOB (1997). The Fifth Five Year Plan (1997-2002), Ministry of Planning, Planning Commission, Government of Bangladesh, p.325.
6.
GOB (2010). The Fifth Industrial Policy, Ministry of Commerce and Industry, Government of Bangladesh.
7.
OECD (1997). Organization for Economic Cooperation and Development, Globalization and Small and Medium Enterprises (SMEs), Vol. 1, Synthesis Report, OECD, Paris 1997.
8.
Mintoo, A. A. (2006). SMEs in Bangladesh, CACCI Journal, Vol. 1.
9.
SEDF (2003). Small Enterprise Development Facilities (SEDF/World Bank): The SME Sector: Taking Stock of the Present Situation, mimeo, Dhaka, 2003.
10.
Sia, M. T. 2003. "SME Finance", Paper Prepared for the Asian Development Bank, mimeo.
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Appendix 1: Communalities 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19
Ratios Operating Profit Margin Ratio Return on Assets Cash Return on Assets Return on investment Current Ratio Quick Test Ratio Cash Ratio Net Working Capital Ratio Debt Equity Ratio Debt Ratio Degree of Operating Leverage Interest Coverage Ratio Net gearing Ratio Asset Coverage Debt Coverage Ratio Asset turnover Ratio Inventory Turnover Ratio Receivables Turnover Ratio Payables Turnover Ratio
Initial 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000
Extraction .802 .937 .747 .639 .670 .661 .903 .841 .977 .620 .979 .815 .938 .917 .744 .685 .812 .665 .852
Extraction Method: Principal Component Analysis. Appendix 2: Rotated Component Variable Ratios 1 Return on Assets .959 Asset Coverage .932 Interest Coverage Ratio .887 Operating Profit Margin Ratio .848 Debt Coverage Ratio .805 Asset turnover Ratio .628 Cash Return on Assets Receivables Turnover Ratio Cash Ratio Quick Test Ratio Net Working Capital Ratio Current Ratio Payables Turnover Ratio Inventory Turnover Ratio Debt Ratio Debt Equity Ratio Net gearing Ratio Return on investment Degree of Operating Leverage 24
Matrix (Factor Loading) Component (Factor) 2 3 4
5
.774 -.773 .768 .716 .698 .599 .913 .854 -.504 .973 .952 .578 .986 Kushagra International Management Review
Entrepreneurial Performance in the Presence of Illegal Firm Activities and Constraining Investment Climate Syed Hasanuzzaman* Mohammad Shoyeb**
ABSTRACT Unfavorable investment climate may drive firms to illegal activities, inefficient investment and/or limited production. Our study attempted to categorize different investment climate variables, relate investment climate to entrepreneurship and examine entrepreneurial performance based on business performance. Our findings show a clear discriminatory behavior of investment climate variables in Sylhet, Bangladesh to ownership type, firm operation and business performance. Thus supports are there for special government and non-government policies to work for a better investment climate in Sylhet, Bangladesh. Keywords: Entrepreneurial Performance, Entrepreneurship, Investment Climate, Factor Analysis, Selection Bias etc.
INTRODUCTION Entrepreneurs and investment climate are two important features of firm performance, industrial expansion and economic growth. However, it is not easy to understand the link between these two. Entrepreneurship is better understood by the functional role of entrepreneurs, such as, coordination, innovation, uncertainty bearing, capital supply, decision making, ownership and resource allocation (Friijs et al., 2002; Jääskeläinen, 2000). On the other hand Stern (2002) defined 'investment climate' as institutional and behavioral environment, both present and expected, that influences the returns, and the risks, associated with investment. Both entrepreneurship and investment climate have macroeconomic phenomena as well as they offer different important micro aspects of macroeconomic performance (Hallward-Driemeier et al., 2006, Davidsson and Henrekson, 2002). In particular, firm performance is correlated with ownership as well as it is influenced by regulatory burdens, corruption, technological and financial infrastructures, banking access and labor market flexibility. However, we cannot ascertain enhanced entrepreneurial activity due to favorable investment climate. According to McClelland (1961) entrepreneurs can maximize economic achievement regardless of macroeconomic conditions and personal entrepreneurial competencies like opportunity seeking, risk taking, persistence, persuasion etc. may defy adverse economic conditions. Many studies have detected both productive and unproductive firm activities when the business environment possesses turbulence, weakness, uncertainty, corruption etc. (Manolova and Yan, 2002; Rehn and Taalas, 2004; Smallbone and Welter, 2001; Aidis and Praag, 2006; Smallbone and Welter, 2009; Welter and Smallbone, 2009). Davidsson and Wiklund (2001) figured that firms work for personal income and wealth besides contributing at both society and venture level as they introduce new products or services. But we can have a legal firm engaged in redistributive works as well as an illegal firm being socially beneficial (Davidsson, 2004).
This study aims to work with the puzzling link between entrepreneurship and investment climate in a resource abundant area of Bangladesh (Joarder et al. 2005 & 2008) and attempts to examine how investment climate can alter business performances in the presence of illegal firm activities, like non-compliance to state laws, unproductive activities etc. Being a developing country, Bangladesh hosts various institutional and structural weaknesses generating wide scopes for corruption, illegal entrepreneurship experience, reluctant entrepreneurship, * Assistant Professor, Deptt. of Economics, Shahjalal University of Science & Technology, Sylhet, Bangladesh ** Graduate Research Fellow, Deptt. of Economics, Shahjalal University of Science & Technology, Sylhet, Bangladesh Entrepreneurial Performance in the Presence of Illegal Firm Activities and Constraining...
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etc. Bangladesh remains among five percent most corrupt countries for long according to surveys conducted by Transparency International, Business International, Political Risk Services, the World Economic Forum etc. and looses about two to three percent of her GDP growth to corruption each year (The World Bank estimates). The World Bank enterprise survey (2002) about the investment climate of Bangladesh has revealed that the highest unofficial payments by the firms goes to the customs agency and then to the tax authorities. Bribing is also found common for infrastructural facilities like gas, electricity and telephone connections. Fernandes (2006) has used data from manufacturing firms in Bangladesh for the period 1999-2000 and found that occurrences of bribe provide negative influence on firm productivity. Several authors like Baumol (1990, 1993); Dallago (1997, 2000); Foss and Foss (2002); Davidsson and Wiklund (2001); Davidsson (2004); Sauka (2008) etc. have analyzed how entrepreneurship can be self-centered, inequality promoting and even resource wrecking through illegal and shadow activities. Hence, for a better understanding of entrepreneurial efficiency in the presence of differentiated investment climate variables and illegal firm activities we have to rely upon the analysis of investment climate and firm performance. EMPIRICAL METHOD Practically investment climate can be linked to firm's optimal investment pattern (Gilchrist and Himmelberg, 1998) or firm-level productivity (Bastos and Nasir, 2004) or firm financial planning for the maximum growth rate (Demirgüç-Kunt and Maksimovic, 1998). Following Dao (2006) and Dollar (2003) we asked entrepreneurs to opt for constraining factors from a broad list of investment climate variables selected from established literatures (Abel and Blanchard, 1986; Bond and Meghir, 1994; Beck et al., 2000; Djankov and Murrell, 2002; Clarke, 2004; Bastos and Nasir, 2004; Hallward-Driemeier et al., 2006; Sekkat and Veganzones-Varoudakis, 2007; etc.). There was no ranking among the constraints and participants could select any number of them. For each factor, respondents circled a number on a scale that ranged from one (not at all concerned) to three (somewhat concerned) to five (very concerned). However, the order of presentation of these items within the survey was uniform across all respondents and we are unable to test for the presence of order effects. The questions related to constraints are like as follows:
Do you face problems in labor management or had to suffer labor scarcity? Do you feel your business is risky, particularly regarding returns? Ever felt lack of credit? etc. None of the question materials mentioned or described any of the constraints nor attempted to gauge individual awareness of any production technology so that responses rely upon the respondent's knowledge at the time of the survey only. The constraints with prominent votes are reported in table - 1, where results are separated based on gender of the participants. However, we have chosen only eight constraints with significant common choice: Risk perception, Labor management, Credit constraint, Power cut, Lack of security, Corruption, Communicational hazards and Lack of alternative investment opportunity. Entrepreneurship can be viewed as new venture creation or small business management (Gibb, 1999) or as the non-mechanical factor of production (Baumol, 1987; Pirich, 2001; Kirby, 2003) who reinvests business income into its venture, aiming at business development (Scase, 1997). Firm size, business turnover and business financial success can be used as entrepreneurial performance measures (Van der Sluis et al., 2003, 2005). We concentrate on the sale expansion as an indicator for firm performance as profit cannot be a good scale in our case for firms engaged in illegal activities who suppress data. About 121 firms out of 132 have reported profits so low that they come up with negative net profits. Also the small and cottage type firms in our sample produce heterogeneous products for which an analysis of output is cumbersome; while cost is used to reflect firm scale of production and resource usage. Hence we care for firm's monthly sale as the indicator business turnover. The set of correlates comprises conventional investment climate variables related to imperfections in commercial, legal and physical infrastructures and various aspects of entrepreneurial activities following the conceptual framework of the Global Entrepreneurship Monitor (GEM) as described by Reynolds et al. (2002). 26
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However, enterprises adopt various strategies, not necessarily legal always, to defend, avoid and survive socioeconomic perplexes in the form of institutional inefficiency, lack of legislation and rules, implementation deficiencies etc. Hence, firms, particularly small and medium, operating in a country like Bangladesh amidst widespread corruption, institutional flaws, infrastructural deficiency, poor governance etc., can be opportunity and goal seekers and thereby be engaged in illegal activities. Doubtful firm compliance thus raises questions about a proper definition of firm performance and the existence of some unauthorized firms (either unregistered or operating without legal certificates and identifications) in our sample forced us to consider their alternative business motivations. This new twist in the relationship between ownership, investment climate and firm performance suggests a sample selection problem. Our outcome equation will try to identify how firm's sale performance or motivation for business expansion (Y) responses to the fluctuations in measurable personal characteristics (Xi), investment climate variables (ICi) and firm specific characteristics (Zi) as suggested by Van der Sluis et al. (2003 & 2005). Yi is only observed if the individual firm, owned by respondent i, is having increased turnover or expansion motivation and if it has a formal public tax identity. Hence we can assume that Y is observed if and only if a second, unobserved latent variable exceeds a particular threshold: Vi* = Wia + ei where,
Vi
1 if 0 othersise
Vi * 0;
As described earlier, we have defined V = 1 if the individual firm is operating as a formal taxpaying firm. We further assume that Y and V have bivariate normal distribution with correlation coefficient ?. The selection model includes major obstacles to production as well as type of entrepreneurships and a measure for firm size. Data We have collected data in several field visits in April-June, 2013 in two BISIC industrial zones in Sylhet1 : Khadim & Gotatikor. Because our questionnaire includes questions about illegal firm operations, a good quantity of them was returned with unanswered parts. Hence though we started with a random sampling method, we had to broaden our circle of sample out of the industrial zones following a snow-ball approach and collect data from adjacent areas. A total of 170 data were collected, but due to unfulfilled questionnaires we can use only 132 of them. Only small and medium scale firms are included in our study. Description of Variables Standard income and demographic variables (age, education, race, gender, training, occupational records etc.) are incorporated as are several attitudinal variables concerning firm production and compliances. These include firm's credit information, ownership pattern, different registration profiles etc. Proprietorship captures the phenomenal difference between entrepreneurs and takes the value 0 for partnership type of entrepreneurs, while 1 is reserved for proprietors or single owners. Among 132 firms 103 are having single owners (proprietors). About 35 percent firms are experiencing improved turnover records, while about 72 percent are showing intentions to expand business. The capital labor ratio is higher for the firms having better turnovers (3.31). It is 0.78 for firms with no improvement in their sales. Also the successful firms are having more than five times cost of production, four times amount of loan and twice employment compared to firms failing to expand their sales. But firms have high standard deviation regarding them. About 22 percent of 85 migrated entrepreneurs are successfully operating their business, while this statistics is about 60 percent for the local entrepreneurs. Age records show entrepreneurs having success and failure are of pretty similar age (36 years). 1
Bangladesh Small & Cottage Industries Corporation (BISIC) has established these two zones here. The Gotatikor industrial zone started its journey in 1978 comprising about 25 acres land and 72 firms. The Khadim industrial zone became operational in 1989 with 28 acres land and 78 firms. Most of these firms are engaged in small scale productions like textile mills, food processing, aluminum products, cosmetic products, chemical products, engineering tools etc.
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Table 1: Perceptions for Production Constraints in Percentage Constraints Risky returns Periodic labor shortage Credit constraint Power cuts Lack of security Corruption Communicational hazards Lack of alternative investment opportunity
Male (%) 38.60 12.28 19.30 36.84 15.79 21.05 35.09 26.32
Female (%) 39.47 23.68 25.00 40.79 15.79 22.36 36.84 31.58
Lack of skilled labor Unfavorable public policy Increased competition/Shrinking market Market imperfection Inefficient market intermediaries Others
5.26 1.75 6.84 5.26 8.77 -
6.58 5.26 7.79 5.26 8.53 -
Empirical Findings The investment climate variables have significant correlation coefficients (Table - 5, Annex. 1) with none receiving a high value like 0.9, for which none of the eight questions should be eliminated. The Kaiser-Meyer-Olkin measure, the Kaiser's (1974) recommendation and the Bartlett's test of sphericity supports factor analysis for our data. We have incorporated the principal component analysis as an extraction process. Table - 10 (Annex. 1) lists the eigenvalues associated with each liner component (factor) before extraction, after extraction and after rotation. We have eight linear components for our eight factors within the data set and the eigenvalues are displayed in terms of the percentage of variance explained. The first few factors explain relatively large amounts of variance (especially factor 1) and the factor selection is supported by the scree plot (Fig. 1, Annex. 2) and the rotation of the factor structure. The first factor concerns corruption, security problem and communicational constraints, which are related to institutional lacking. We therefore label the first factor as institutional flaws. The questions for factor 2, i.e., high probability of risk, credit shortage, weakness in labor management and lack of investment opportunities are usual firm level production difficulties. Hence, we call factor 2 the conventional flaws. The single question that loads highly on factor 3 is related to power problems in production and we name it the power flaws. As we start linking the constraining investment climate variables to business performance, we confront a positive and significant rho () that justifies our assumption of selection bias in the sample and portrays an incremental probability of sale expansion due to firm noncompliance as well. Table - 2 shows us the results of Heckman probit model judging the difference between firm performances along with the marginal effect of the kth element of x on the conditional expectation of y as described by Sigelman and Zeng (1999). Table 2: Estimated Coefficients of Entrepreneurial Performance Models Outcome Equation Proprietorship Capital-Labor ratio Cost
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Sale Expansion 0.48 0.34 –0.06 0.70 0.26 0.35
Marginal Effects 0.32
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Outcome Equation
Sale Expansion
Business loan
0.01 0.75 –0.30a 0.00 –0.19 0.19 0.14 0.34 –0.81b 0.03 –2.72 0.30
Institutional flaws Conventional flaws Power flaws Firm size Constant
Marginal Effects
–0.30 –0.18 0.11 –0.66
Selection Equation for Illegal Entrepreneurship Entrepreneur's age Entrepreneur's age2 Proprietorship Institutional flaws Conventional flaws Power flaws Local entrepreneur Firm size Constant Wald test (rho) = 0
–0.04 0.72 0.00 0.71 0.67b 0.02 -0.02 0.86 -0.04 0.70 0.11 0.29 -0.83a 0.00 -0.59a 0.00 1.68 0.41 2 (1) = 5.76b
a, b & c represents significances of level 1, 5 and 10 percents respectively and p-values are reported in italics It can be inferred from our findings that businesses owned by single owners are promoting illegal firm operations intensively compared to partnership type of entrepreneurship. But it is not certain that this can solely help gain extra benefit regarding firm's business expansion. Only institutional flaw is the most influential investment climate variable that alters firm performance. Therefore, corruption, security problem and communicational constraints are more hazardous for firms. It is interesting to note that where conventional flaws also constrain firm performances, power flaws are seemingly enhancing. This may be due to the use of natural gas in production related works that is cheap and is supplied with fewer disruptions; whereas the use of electricity is limited mainly in non-productive firm activities. Heterogeneous firm technology may leads to insignificance of both these constraints. Firm size is another important variable that significantly drives away firm's advantages in sale. As we have defined firm size through number of labors, it is rather obvious. Lastly, if the entrepreneur has a local background then it provides a strong disincentive to indulgence in illegal firm operations. This probably reflects the relationship between social prestige and firm compliance. Entrepreneurial Performance in the Presence of Illegal Firm Activities and Constraining...
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A falling insignificant capital labor ratio is predictable due to high concentration of small and cottage firms in our sample. Both firm scale of production (cost) and amount of business loan have positive impacts on firm performance though they remain insignificant. Entrepreneur's age shows an expected nonlinear relationship to firm compliance though being insignificant. Working with illegal firm operations obviously leads us to data deficiency. Thus a test to substantiate our result is a difficult task. However, we also collected a simple perception data about which firms had the intention to invest more. Thus we can examine an intention model. A number of studies have indicated that business growth and the entrepreneur's intentions are closely related (Davidsson, 1991; Kolvereid, 1992; Cooper, 1993; Cliff, 1998; Wiklund et al., 2003). Table 3: Probit Regression for Business Expansion Intention Business Expansion Intention
[Probit Coefficients]
[Probit Marginal Effects]
Entrepreneur's age
0.05 0.65
0.01 0.65
Entrepreneur's age2
0.00 0.93
0.00 0.93
-0.08 0.82
-0.02 0.82
Proprietorship Illegal Entrepreneurship
0.64b 0.05
0.18b 0.05
Local entrepreneur
0.45 0.17
0.11 0.14
Capital-Labor ratio
0.02 0.82
0.01 0.82
Cost
0.72b 0.01
0.19b 0.01
Business loan
–0.01 0.69
0.00 0.69
Institutional flaws
–0.50b 0.01
–0.13b 0.01
Conventional flaws
–0.15 0.26
–0.04 0.26
0.10 0.52
0.03 0.53
Firm size
–1.57a 0.00
–0.42a 0.00
Constant
–6.16b 0.05
Power flaws
--
a, b & c represents significances of level 1, 5 and 10 percents respectively and p-values are reported. Heckman probit model yields an insignificant rho (?) value suggesting absence of selection bias in the intention model. A slightly modified probit model (Table - 3) supports most of our findings. 30
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CONCLUSION A differentiated behavior of the investment climate variables coexists with illegal entrepreneurial activities in Sylhet. The analysis of investment climate here provides us with a clear picture why entrepreneurs, specially, those who invest in small and cottage industries, are not enthusiastic in investing more. It is clear that business obstacles caused by lack of governance along with lack of large scale public and private investments in infrastructure are hampering all the investors. One special feature of such constraints is that they behave similarly to all and individual efforts are close to meaningless against them. Though entrepreneurs put immense importance on financial and power related constraints, it is retrieved that they are not limiting firm performances and, specially, illegal firm operations are more evident among small scaled firms. We conclude that institutional constraints leads small and cottage firms get involved with illegal activities to keep up or expand their business. Thus in a very limited sample and for a particular type of investment climate we have shown that entrepreneurial investment in illegal activities are inspired by production obstacles. Our findings provide justification for ease of public laws and regulations, particularly for the small scale business. Better governance along with higher public support for enhanced security and better infrastructure will motivate entrepreneurs expand their business. REFERENCES 01. 02. 03. 04. 05. 06. 07. 08. 09. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20.
Abel, A. and Blanchard, O. (1986). "The Present Value of Profits and Cyclical Movements in Investment." Econometrica 54: 249-274. Aidis, R. and Van Praag, M. (2007). "Illegal entrepreneurship experience: Does it make a difference for business performance and motivation?" Journal of Business Venturing, 22, 283-310. Bastos, F. and Nasir, J. (2004). "Productivity and the Investment Climate: What Matters Most?" World Bank Policy Research Working Paper Series 3325, Washington, D.C. Baumol, W. J. (1986). "Entrepreneurship and a Century of Growth", Journal of Business Venturing, 1(2), 141-145; Baumol, W. J. (1990). Entrepreneurship: Productive, Unproductive and Destructive. Journal of Political Economy, 98(5), 893-921. Baumol, W. J. (1993). Entrepreneurship, Management and the Structure of Payoffs. London: MIT Publisher. Clarke, G. (2004). "Why Don't African Manufacturing Enterprises Export More? The Role of Trade Policy, Infrastructure Quality and Enterprise Characteristics." Processed. Washington DC: The World Bank. Cooper, A., 1993. Challenges in predicting new firm performance. Journal of Business Venturing 8, 241 - 253. Dao, Minh Quang (2008). The Impact of Investment Climate Indicators on Gross Capital Formation in Developing Countries. Journal of Developing Areas, Vol. 65: 155-163. Davidsson, P (2004a). Researching Entrepreneurship. New York: Springer. Davidsson, P and J Wiklund (2001). Levels of Analysis in Entrepreneurship Research: Current Re-search Practice and Suggestions for the Future. Entrepreneurship: Theory & Practice, 25 (4), 81. Davidsson, P and M Henrekson (2002). Determinants of the prevalence of start-ups and high-growth firms. Small Business Economics, 19 (2), 81-104. Dollar, David, Mary Hallward-Driemeier, and Taye Mengistae. (2003). "Investment Climate and Firm Performance in Developing Economies." World Bank, Development Research Group, Washington, D.C. Fernandes, AM (2006). Firm Productivity in Bangladesh Manufacturing Industries. WPS 3988, WB. Friijs, C, T Paulsson and C Karlsson (2002). Entrepreneurship and Economic Growth: A Critical Review of Empirical and Theoretical Research. Östersund, Sweden, Institutet för tillväxtpolitiska studier. Hallward-Driemeier, Mary, Scott Wallsten, and L., Colin Xu (2006). "Ownership, investment climate and firm performance: Evidence from Chinese firms." Economics of Transition, Volume 14(4) :629-647. Jääskeläinen, Miko (2000). "Entrepreneurship and Economic Growth." Helsinki: Institute of Strategy and International Business. Joarder, M.A.M. & Hasanuzzaman, S. (2008) Migration Decision from Bangladesh: Permanent versus Temporary. Asia Europe Journal. 6 (3). p. 531-545. Kolvereid, L. (1992). Growth aspirations among Norwegian entrepreneurs. Journal of Business Venturing 7,209 - 222. Manolova, TS and A. Yan (2002). Institutional Constraints and Entrepreneurial Responses in a Transforming Economy: The Case of Bulgaria. International Small Business Journal, 20 (2), 163-184.
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21. 22. 23. 24. 25. 26. 27. 28. 29. 30.
Pirich, A (2001). An interface between entrepreneurship and innovation: New Zealand SMEs perspective. The 2001 DRUID Conference, Aalborg, Denmark. Rehn, A and S Taalas (2004). Znakomstva I Svyazi (Acquaintances and connections) - Blat, the Soviet Union, and mundane entrepreneurship. Entrepreneurship and Regional Development, 16 (3), 235-250. Reynolds, P, WD Bygrave, E Autio, LW Cox and M Hay (2002). Global Entrepreneurship Monitor: 2002 Executive Report. London et al. Sauka Arnis (March 2008) "Productive, Unproductive and Destructive Entrepreneurship: A Theoretical and Empirical Exploration". William Davidson Institute Working Paper Number 917. Scase, R (1997), "The Role of Small Businesses in the Economic Transformation of Eastern Europe: Real but Relatively Unimportant". International Small Business Journal, 16, 113-121. Sekkat, Khalid and Veganzones-Varoudakis, Marie-Ange (2007). "Openness, Investment Climate, and FDI in Developing Countries." Review of Development Economics, 11(4): 607-620. Sigelman, L. and Zeng, L. (1999) "Analyzing Censored and Sample-Selected Data with Tobit and Heckit Models." Political Analysis, vol 8(2), pp. 167-182. Smallbone, D and F Welter (2009). Entrepreneurship and small business development in post-socialist economies. London, Routledge. Stern, N. (2002). "A Strategy for Development." The World Bank, Washington, DC. Van der Sluis, J, CM van Praag and W Vijvererg (2003). Entrepreneurship Selection and Performance: A MetaAnalysis of the Impact of Education in Industrialized Countries. Tinbergen Institute Discussion Paper. Amsterdam.
Constraints 1 2 3 4 5 6 7 8
Annex. - 1 Table 4: Correlation Matrixa for Constraints Correlation Matrix for Constraints 3 4 5 6
1
2
1.000 .137 .238 -.018 .137 .039 .072 .078
.137 1.000 .261 .205 .291 .175 .232 .160
.238 .261 1.000 .039 .071 -.016 -.018 .162
.058
.003 .001
1 2 .058 3 .003 4 .418 5 .058 6 .329 7 .206 8 .186 a Determinant = .428
.001 .009 .000 .022 .004 .033
.327 .210 .428 .419 .031
-.018 .137 .205 .291 .039 .071 1.000 .076 .076 1.000 .085 .545 -.010 .128 -.094 -.045 Sig. (1-tailed) .418 .058 .009 .000 .327 .210 .194 .194 .164 .000 .452 .071 .142 .303
7
8
.039 .175 -.016 .085 .545 1.000 .190 -.199
.072 .232 -.018 -.010 .128 .190 1.000 -.001
.078 .160 .162 -.094 -.045 -.199 -.001 1.000
.329 .022 .428 .164 .000
.206 .004 .419 .452 .071 .014
.186 .033 .031 .142 .303 .011 .493
.014 .011
.493
Table 5: KMO and Bartlett's Test Kaiser-Meyer-Olkin Measure of Sampling Adequacy. Bartlett's Test of Sphericity
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Approx. Chi-Square df Sig.
.570 109.114 28 .000
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Table 6: Total Variance Explained Con- Initial Eigenvalues Extraction Sums of straSquared Loadings ints Total % of Var. Cumul. % Total % of Var. Cumul. % 1 1.939 24.236 24.236 1.939 24.236 24.236 2 1.452 18.144 42.380 1.452 18.144 42.380 3 1.058 13.229 55.609 1.058 13.229 55.609 4 .984 12.303 67.912 5 .868 10.852 78.763 6 .725 9.056 87.820 7 .560 7.005 94.825 8 .414 5.175 100.000 Extraction Method: Principal Component Analysis.
Rotation Sums of Squared Loadings Total % of Var. Cumul.% 1.781 22.267 22.267 1.521 19.012 41.279 1.146 14.330 55.609
Table 7: Component Matrixa Constraints 5 Lack of security 6 Corruption 2 Risky returns 7 Communicational hazards 8 Lack of alternative investment opportunity 3 Credit constraint 1 Periodic labor shortage 4 Power cuts Extraction Method: Principal Component Analysis. a 3 components extracted.
1 .755 .683 .660 .422
Component 2
3
-.483
.674 .635 .432 .866
Table 8: Rotated Component Matrixa Constraints
Component 2
1 3 6 Corruption .822 5 Lack of security .788 7 Communicational hazards .500 3 Credit constraint .696 8 Lack of alternative investment opportunity .626 1 Periodic labor shortage .546 2 Risky returns .540 4 Power cuts .910 Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. a Rotation converged in 4 iterations. Entrepreneurial Performance in the Presence of Illegal Firm Activities and Constraining...
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Table 9: Component Transformation Matrix Component 1 2 3
1 .868 -.387 -.310
2 .383 .921 -.074
3 .314 -.054 .948
Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. Table 10: Component Score Coefficient Matrix Constraints
Component 2 .358 .324 .456 -.060 .007 -.161 .072 .435
1 1 2 3 4 5 6 7 8
Periodic labor shortage Risky returns Credit constraint Power cuts Lack of security Corruption Communicational hazards Lack of alternative investment opportunity
.107 .145 -.069 -.111 .439 .474 .309 -.141
3 -.172 .287 .153 .822 .015 .007 -.251 -.165
Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. Component Scores. Annex. - 2 Figure 1: Scree Plot
Scree Plot 2.5
2.0
1.5
Eigenvalue
1.0
.5
0.0 1
2
3
4
5
6
7
8
Component Number
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Conceptualizing and Testing Advertising Demand Grid: A Prospective Tool for an Effective AD-Designing Dr. Braje sh Kumar* Dr . G ou ran ga Patra**
ABSTRACT We, in this paper, have developed and examined a relationship which is based on the socio-economic status of the people and the expected demand or preference for advertising in a low involvement product category as correlates to each other and that which create a strong reflection for an effective advertising of low involvement products in India. In this backdrop an Advertising Demand Grid was developed by the researchers which is primarily based on the matrix of relationship between product involvement levels and socio-economic status of the respondents and the theoretical findings of the researchers in different parts of the world especially those who are industrially and commercially more advanced and the expectations or predictions of the proposed grid are tested in a culturally vibrant but geographically isolated region of India. Within these limitations our research supports the Advertising Demand Grid in general in case of low involvement product advertising and by proxy we can presume that the proposed grid may well be valid for the high involvement product advertising. Keywords: Advertising Demand Grid, Effective AD-Designing, Low Involvement Product Advertisement etc.
INTRODUCTION Advertising is an essential tool of modern marketing. Wells et al. (1995) defines that "advertising is paid non personal communication from an identified sponsor using mass media to persuade or influence an audience." Advertising represents customers' key part of daily life and influences their purchase intentions (Lafferty & Goldsmith, 1999). For this reason, advertisers invest billions of dollars in advertising; no doubt they want to achieve advertisement effectiveness. A large amount of consumers get information that distributed free by sellers through advertising. Information is developed well by mass media so that consumers can get messages easily and fast. Advertising powerfully shape consumer preferences and persuade people to buy what they would not otherwise buy. Advertising simply provides information to assist consumer decision making. Even if advertising does not work immediately, repetition ensures its effectiveness. Consumers are ultimate rational in making decisions, so ads need to provide at least one logical reason to purchase. There are two prerequisites for consumers to engage in the central route of persuasion. First, consumers must have ability to scrutinize a message carefully. Factors affecting consumers ability to a process a message include, consumer knowledge(wood & lynch.2002) the amount of distraction present in the environment( Petty et,al,1981)5 and the number of times the message is repeated( Cacippo & Petty,1979)6. Therefore, it implies the imperatives of consumers' competence in acquiring, examining and deriving meaning for an effective communication and higher appeal of an ad campaign. In other words getting exposed to media where advertisements appear; educational and cultural maturity to decode and appreciate ads; and market accessibility to get motivation for processing the messages aired in ads are must for any successful advertising. We hypothesise that economic and social status of the consumers determine the quality,range and intensity of ad exposure; ability to decode and appreciate ads and involvement level in message processing. LITERATURE REVIEW While no consensus exists, many researchers define involvement as the extent to which a stimulus or task is relevant to the consumer's existing needs and values(Buchholz & Smith, 1991). Laczniak, Muehling, & Grossbart (1989) reviewed past conceptualizations in advertising studies and established two basic tenets of involvement in * Assistant Professor, Department of Commerce, Assam University, Silchar, Cachar, Assam, India ** Assistant Professor, Department of Business Management, C V Raman College of Engineering, Bhubaneswar, India Conceptualizing and Testing Advertising Demand Grid: A Prospective Tool for an Effective AD-Designing
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advertising. As consumers become more involved they will pay more attention to the advertisement's message and focus more on brand processing as opposed to non-brand processing. High involved consumers use more criteria for choice making (Mitchell 1989); search for more information (Beatty, and Smith 1987); know more about the alternatives (Petty and Cacioppo 1983, Maheswaran and Levy 1990); process relevant information in detail (Chaiken 1980)17; and will form attitudes that are more resistant to change(Petty et al 1983). Active brand processing is captured by High Involvement Processing. High Product Involvement (also named the Persuasive Hierarchy model) assumes that the consumer is taking in brand information, forming preferences based on this information, then buying the most preferred brand and when information and their designing presented in an ad is of high appeal, it helps to get consumer involved in the information and that prompts consumer to process the information for forming preference for a brand. In addition several researchers have found that in high economic status people are more realistic in nature (Havitz and Haward,1995) and they do not have much more spare time to concentrate on advertising. So active processing in advertising and rational appeal of advertising is more preferable (John and Seth,1969). Krugman (1965) suggested that at the higher level of involvement consumers produce "personal connections" or "bridging experiences," whereby they relate the advertisement content to meaningful aspects of their own life. Greenwald and Leavitt (1984) built upon this conceptualization, stating that "the audience experiences 'personal references' or 'connections' to the advertising message, [which] corresponds to the higher level of involvement and elaboration. Though their exposure level is high and more brand loyal in nature and generally they are more quality conscious rather than price so while the nature of different advertising medium they prefer print advertising because they are looking for specific attributes of advertising (Petty and Cacioppo, 1995) where from they can get more information and to get them in a simplified representation. Though, product is high involvement in nature so feeling advertisement is more effective to get consumer attention on ad and on product purchasing decision (Mehta, 2006). In contrast, the Low Involvement Hierarchy is characterized by low involvement in products, such as purchasing convenience goods. Brand preferences are formed after purchase or trial, rather than through advertising exposure before the purchase. In low involvement product advertising -for higher economic status people- they usually favor prestigious brands and items, due to less spare time and higher level of awareness, advertisers apply informational advertising appeal (Aaker, David A & Donald Norris, 1982) to sustain and promote their interest level. In this situation repetition of advertisement is more important (Sawer & Tellis,(1988) with some specific attributes to refine the awareness level of consumers. In spite of these facts, in case of low involvement products which are habitual buying in nature (Gbadamosi, 2009), less involving and repeated buying, and so memorizing a brand is very difficult for the people having higher economic status. They have less time to spend on a message with fuller concentration. At the same time store display at the point of purchase highlighting product attributes in store works as an effective advertising tool. The moderate economic status people where income is limited and budget is also moderate they are mostly pricing conscious. They have more spare time and have a chance to get more exposure at the same time. On the other hand where high involvement products are concerned facing higher price and endurance, buyers of this moderate group go for situational and occasional buying. Due to high dissonance and veil of ignorance on their part, advertisers always follow such type of advertising where positive interpretation of message becomes more important to create awareness (Wright, Alice.A.and John,G,Lynch ,Jr1995), conducive buying environment and to increase brand loyalty. One of the important finding in this regard states that though moderate economic people belong to middle class of the society so the cultural orientation and occasional approach (Muller,2004) is more paying in case of the high involvement product advertising. In context of the low involvement product advertising for the moderate economic class having limited budget along with higher spare time to get exposed to the media and the market place. They have strong sense of social & cultural values, attachments and likings for elaborated ad design which covers materials that satisfy their comprehensive emotional and informational canvas of advertising demand which also includes high price sensitivity posited into the products. It is helpful in this situation to go for emotional appeal of advertising which is more favorable in this regard. It increases current level of exposure and awareness for products and brands. Several researchers have also reported that television and outdoor advertising is more important in this situation for it 36
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increases the involvement level and responses of consumers towards advertising through the application of music, message and models. In low-involvement situations, Petty & Cacioppo(1983) and (Smith,1991)studied the effects of message repetition on awareness, recall, and attitude formation. They found that in low-involvement situations, repeating different versions of an advertisement prevented early decay of advertising effects. Vakratsas and Ambler (1999) concluded that habit and affect are much more important than cognition for low involvement products. Consumers express low involvement levels for products which are generally low priced, have simple features and low perceived risk ( Saxena 2002;Kotler 2002). They do not show strong loyalty to brands of these products, and do not perceive price as an indication of their quality. If we look at advertising exposure of low economic status people towards high involvement products it is found that without any compulsive demand under occasional necessity for such product they are not prompted to go for easy buying. As it is commonly known that in the low economic status cases where low income, low exposure and low attention level are common. It is necessary to set advertising with emotional touch and comprehensive information base to make it effective. In the present scenario where a high percentage of people belong to low and modeate economic status and the buyers of low involvement products, as a result it is a big challenge for the advertisers to build up the proper advertising strategy and media mix to create effective advertising. Though the low economic status people stand low at income and social standing, so their expectation and exposure levels are also low( Jha,2000) but at the same time they belongs to the group having high fantasy attitudes towards products and product advertising. On the basis of such characteristics the advertisers develop such advertising strategy that increases their expectation level and awareness level using elaborative advertising design, colorful background and storytelling ads, and simplicity & straightforwardness in message designing (David W. Richard,1990), which increase the visualization and generate interests for the products and the ads side by side another important phenomena is that low economic status people are more conservative in nature due to unavailability of different media the information gathering sources are also limited and this is the reason behind the low attention and the low consciousness level of consumers in this group (Kastenholz & Young(2003). To overcome these problems and increasing the exposure level of consumers, the advertisers place more emphasis on outdoor and television media. For this they take help of regional channels, well known models (Razzouk et.al,2003)40. and pleasant music and folklores that increase exposure, expectation and generate internal feeling of emotions in their mind for the ads. In many advertising response models, the degree of consumer involvement is expected to influence both the amount and quality of the consumer's cognitive response. In terms of the amount of cognitive response, involved consumers engage in more labored information search and acquisition strategies. When actively searching for product-related information, interest in brand advertising is at a maximum. In addition to increased cognitive efforts, most advertising models predict a qualitative difference in message processing as involvement increases. Involved consumers are more likely to process brand information at a "deep level" where they actively evaluate the message. These cognitive evaluations can be directed towards the importance, persuasiveness, or relevance of the advertisements content (Smith, 1991). OBJECTIVES 1. To develop a grid that contains the studies relating economic and social status of the person exposed to ads and effectiveness of the ad campaigns in both the high&low involvement product categories 2. To test the grid in low involvement product category in a particular geografical area.
Scope and Limitation of the Study The present study is about the mechanism of an effective advertising in low involvement product category. It is conducted in a geographically isolated region in the state of Assam in North -East India which is on the other hand highly exposed to the media and the wordly aspirations of the present time. Findings of the study therefore are very much confined to the localised conditions. Conceptualizing and Testing Advertising Demand Grid: A Prospective Tool for an Effective AD-Designing
37
METHODOLOGY OF THE STUDY Examining the rich literature in this field, we have In the present study we have selected a region of North East India i.e. Cachar district of Assam which is neither fully exposed nor fully isolated from the mainland of commercial and cultural life in India. But from the statistical records it is found that this region belongs to the people coming from diverse cultural and economic background. In this sense, we are trying to find out here the relative importance and impacts of individual components of advertisements on different socio-economic group of consumers in terms of interest, likings and involvements that ensure the effectiveness of an ad design subject to the exposure level of consumers. The present study is about the testing of different advertising components and its design on consumers( based on AG) in comparison to different socio-economic groups with regards to low involvement products advertising (i.e., the Fast Moving Consumer Goods advertising). The composition and characteristics of the population set for the present study entails the categorization of members on the basis of urban-rural duality. And next the other bases of classification are educational attainment, income level and exposure level to represent the socio-economic status of the consumers and their level of media exposure. Regarding the data collection our basic units of data are individuals. Individuals have been randomly chosen from urban and rural segments. Individuals as the primary unit of the present study has first been selected using convenient sampling method and the data collected were set forth for selecting some of them randomly as sample for the present study. To test the significance of difference of interest level shown by the respondents towards the different Ad components recorded in the three different combinations of socio-economic status and higher and lower interest levels. 'A- statistics' is used for this purpose. DATA ANALYSIS, RESULTS AND INTERPRETATION The study is based on primary data and we have collected 450 data on the basis of convenient sampling design, then 310 data were selected randomly to make the present sample. Selected data have been classified into three groups viz; high socio-economic group, medium socio-economic group and low socio-economic group. The representative data in different groups are 73( in high),155(in medium) and 81(in low). On the basis of above discussion we developed a relationship which was based on economic status and product involvement levels as correlated to each other and create a strong reflection for effective advertising of low involvement products and high involvement products. The socio- economic status are divided into three groups i.e.- high socio-economic status, middle socio-economic status and low socio-economic status. Product involvement is classified as high product involvement and low product involvement. On the basis of these components we developed an Advertising Demand Grid based on the matrix of involvement and socio-economic status. Advertising Demand Grid in the present context represents a framework that gives an idea about how under the combined impact of socio -economic status and the levels of product involvement consumers interest or likings for advertising is influenced and determined. Probability of liking or interest their of is used as the probable demand for advertisings in a particular category of products. Though, our study is based on socio-economic groupings and their expectation level in the low involvement product advertisements. The socio-economic group is defined in the present study on the basis of income level, educational attainment and the exposure level of the respondents. We have three groups based of these criteria as high, medium and low. Based on the criteria above the socio-economic grouping has been divided into three levels which details are noted below.
Table 1: Socio Economic Grouping Socio-economic Status
Income Level
Educational Attainment Level
Media Exposure Level
High
More than 20000/
Medium
From 10000 to 20000
Television, all print media, outdoor media. Television and outdoor media.
Low
Upto 10000
From inter college onwards Upper primary to intermediate Primary level
Television or outdoor media.
Source: Developed by the Researcher 38
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On the basis of extensive survey of available scholarly studies relating to the present study are summarized and designed in a grid form and presented above. Close examination of the Advertising Demand Grid (ADG hereafter) within the given space of derived matrix thereof give us some concrete clues regarding the implications of the present ADG given above. These are enlisted hereunder: (1)High demand for classified informational ad,(2) Demand for repeated advertising,(3) Demand for instore display on point of purchase.(4) inclination for price indicating ads.(5) Demand for emotional ad(6) Demand for familiar background and engrossing tunes.(7) Demand for music and folklores in ad design.(8) Demand for cultural specific ad design.(9) Demand for entertaining cues. (10) Demand for high story contents in message design. RESULTS AND THEIR INTERPRETATION For the purpose of the analysis and interpretation of data, we have used the matrix of interpretation of scored data on interest levels shown by the respondents for different ad components. The same is presented below.
Table 2: Matrix of Levels of Socio-economic Status and the Interest Levels of the Respondents with Regard to an AD Components
Interest level score
high interest level scoring respondents for different ad components (C1)
low interest level scoring respondents for different ad components(C2)
High socio-economic group(R1)
(Number of respondents in the combination of R1 &C1)
(Number of respondents in the combination of R1C2)
Medium group(R2)
(Number of respondents in the combination of R2C1)
(Number of respondents in the combination of R2C2)
(Number of respondents in the combination of R3C1)
(Number of respondents in the combination of R3C2)
Socio-economic group
socio-economic
Low socio-economic group(R3)
Table 3: Matrix of Equations that must be Satisfied to Support the Expectations of Advertising Grid
the
AD Components
Equation that must be satisfied to support the expectation of Advertising Demand Grid
Message Repetitive Television advertising Model Music Packaging Brand Cul ad- design In-store display
R1C1, R2C2, R3C2 R1C1,R2C1,R3C1 R1C2, R2C1, R3C1 R1C2, R2C1, R3C1 R1C1, R2C1, R3C1 R1C1, R2C2, R3C2 R1C2, R2C1, R3C1 R1C1, R2C1, R3C1
> > > > > > > >
R1C2, R2C1,R3C1 R1C2,R2C2, R3C2 R1C1, R2C2, R3C2 R1C1, R2C2,R3C2 R1C2, R2C2, R3C2 R1C2, R2C1, R3C1 R1C1, R2C2,R3C2 R1C2, R2C2,R3C2
Source: ADG matrix The interpretation of the table: R1C1 > R1C2 means that the number of respondents showing high interest in the message of an ad falling in the High socio -economic class and the High Involvement Product category should be more than the number of respondents from the same socio -economic class but in the Low Involvement Product category. Being so , it is a sign that the assumption made in the Advertising Grid( AD) is validated. Conceptualizing and Testing Advertising Demand Grid: A Prospective Tool for an Effective AD-Designing
39
Exhibit 1: Advertising Demand Grid (ADG) Product characteristics
involvement
Highinvolvementproduct&consumer characteristics : Central cues(25), Issue relevant thinking, Learning and information, Active brand processing, Durable in nature, Brand loyalty(22),
Highinvolvementproduct&consumer characteristics : Peripheral cues( 25), Perishable in nature, Low price, Attractive packaging, Passive processing, Local initiative(5), Low brand commitment(8) , Habitual purchase behavior(22),Low level of engagement(24), Emotional decision making (33) Habitual buying(37)
High socio-economic status &consumer characteristics : More realistic and highly loyal(7), Critical and examining attitude for the life set up and opportunities, Less leisure time, High expectations(30), Quality consciousness, Less price sensitive, Brand conscious, Higher level of awareness owing to affordability and compulsion for exposure, Favor prestigious brand and fashionable item(31)
Consmers’ Ad-likings and Ad design strategy for an effective advertising in High involvement product category
Consmers’ Ad-likings and Ad design strategy for an effective advertising in low involvement product category
Medium socio-economic status &consumer characteristics : Moderate income, Limited budget, Moderate exposure, More spare time, Higher price consciousness. (15), Expectations limited by budget. Situational influences on buying pattern. High dissonance (36). Veil of ignorance(28) Gender bias(28),
Positive interpretation of the message(3) , Culture orientation towards ads(6)
Backlog commitment in product current level of awareness. Emotional ad appeal (12), TV and Outdoor/ retail display ad(34), Visual cues in ad, Pleasant music in ads, Endorsement in ads(2). Liking for music and folklore(33) Strong sense of value for money (31) Cultural specifications in ads(6)
Low socio-economic status &consumer characteristics : Low income, High spare time, Low exposure(16), Low expectation, High fantasy, High commitment to conventional buying for survival and sustenance(31), Strong sensitivity and simplistic decision rules, Low attention and consciousness.(17). Conservative outlook, Limited information, Low level of living(27),
Occasional search for information and products, Seasonal demand, (36), High dissonance High informational demand, High emotional involvement with products and information
Elaborated advertising design, Celebrated and regional models (14), Entertaining (13), storytelling type, simple and straightforward (1). Outdoor ad (9), Attachment for logo(32), Liking for music and folklore33 Limited demand for elaborated ss information. 29
Level of Socio-Economic Status
Rational appeal ad(26) ,Print ad, More focus on brand quality, Preference for limited number of attributes in ad, Liking for feeling advertisement.(11)
Informational advertising appeal(20), Refine awareness, Repeated advertising(4) , High recall status for brand name, Liking for point of purchase display , Lesser concern for product attribute information(23), Liking for prestige pricing
Source: Developed by the Researcher 40
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Results: Now we present the results and their interpretation of the present study noted below. Table 4: Interpretation of Result with Respect to Message Socio-economic status
High (3)(R1) Medium(2) (R2) Low (1)(R3)
High Interest level (5) (C1) 40 (NOR)1 79(NOR) 37(NOR)
Degree of deviation ( O – E)÷E
.335 .000 .376
Low interest level (2) (C2) 32 (NOR) 76(NOR) 43(NOR)
Degree of deviation ( O – E)÷E
.328 .006 .340
Support(S)/ Not Support(NS) ADG Expectation S NS S
Sandler’s A Statistic 4.35>0.412 insignificant at 2 d. f.
Source: Primary Data NOR : Number of Respondents The ADG explains that consumers in high socio-economic group prefer TV advertising for its high informational value(David &Norris,1982) and accordingly they see ads on TV. Therefore expected value of preference is taken as high in the ADG. Results in the table-3 shows that this is supported by the data more in case of high and low socioeconomic groups but not so in case of middle socio-economic group. We can explain this result in the light of the fact that high income group people are exposed to different TV ads extensively and broad based. They are otherwise also exposed to other media and highly busy with their own preoccupations and getting less time to remain engaged with such media advertising and therefore they concentrate more on message contents of an ad inputs. In case of middle income group difference is extremely low and in this light the assumption of ADG is supposed to be vindicated. Table 5: Interpretation of Result with Respect to Relative Television Advertising Socio-economic status
High (3)(R1) Medium(2) (R2) Low (1)(R3)
High Interest level (5) (C1) 68(NOR) 146(NOR) 77(NOR)
Degree of deviation ( O – E)÷E
.019 .005 .018
Low interest level (2) (C2) 4(NOR) 9(NOR) 3(NOR)
Degree of deviation ( O – E)÷E
.016 .085 .323
Support(S)/ Not Support(NS) ADG Expectation S S S
Sandler’s A Statistic .377
