International Journal of Business and Public Management (ISSN: 2223-6244) Vol. 1(1): 75-84 Available online at: http//:www.journals.mku.ac.ke © MKU Journals, April 2011 Full Length Research Paper Collective efficiency and its effects on infrastructure planning and development for small manufacturing enterprises in Kenya Stephen Irura Nganga1, George Mark Onyango2, Bonaventure Wanjala Kerre3 1Karatina University College School of Business P.O. Box 10101 1957, Karatina, Kenya. 2Maseno University Department of Urban and Regional Planning P.O. Box 40105 Private Bag Maseno, Kenya. 3Chepkoilel University College Department of Technology Education P.O Box 30100 1125 Eldoret, Kenya. Corresponding Author: Stephen Irura Nganga Recieved: February 28, 2011 Accepted: March 15, 2011 Abstract This paper explores the extent of use of collective efficiency among the wood enterprises in Kenya and its effect on the infrastructure planning and development. Small manufacturing enterprises are known to contribute to economic dynamism, entrepreneurship and industrial development in less developed countries. However, they are handicapped by lack of capacity to accumulate capital, develop infra- structure and acquire technologies necessary for competing in a liberalized global market individually. Data was obtained from 284 wood enterprises owner/managers selected through multistage sampling in western Kenya and by use of questionnaires, observation checklists and documentary analysis. Data analysis by regression shows that infrastructure development is affected linearly by collective efforts. The paper recommends that industrial infrastructure planning in Kenya should be informed by the Collective efficiency, Networking, Systems approach and Constructivism paradigms so as to anchor the small manufacturing enterprises in the industrialization process. The paper also recommends that a Jua Kali development authority should be established to address the needs of the small manufacturing enterprises sector borrowing from the export processing zones authority model. Keywords: Infrastructure planning, Collective efficiency, wood enterprises JEL Classification: C30 1.0 Introduction of SMEs from micro to small, small to medium and medium to Small Manufacturing Enterprises (SMEs) (SMEs are used here large enterprises does not seem to be taking place (Lukac, to mean all enterprises engaged with the 2005). manufacture/production of artifacts for sale as a business venture employing less than 50 employees) have been noted to For SMEs to be drivers of industrialization, such transition play a significant role in promoting economic growth in Less becomes a necessity for SMEs in LDCs. Further, the SMEs Developed Countries (LDCs), developing and developed must be self sustaining through technological innovations and countries (Liedholm and Mead, 1999). Small enterprises building competitive advantages in a liberalized global market. contribute to economic dynamism and entrepreneurship and Most SMEs are not able to do this on their own. It has been this paper submits that for sustainable industrial development noted that SMEs in developing countries remain in traditional in LDCs, the SMEs will have to play a pivotal role. As United activities generally with low levels of productivity, poor quality Nations Industrial Development Organization (UNIDO, 1998) products and serving small localized markets and therefore puts it, sustainable industrial development is a process of cannot accumulate capital for their growth, infrastructure developing Land, Cities, Businesses and communities to meet development and acquisition of modern technologies. Since the needs of the people or nation, without compromising on the most SMEs in LDCs are not able to build competitive ability of future generations to meet their own needs. advantages on their own and benefit from economies of scale, Consequently, in LDCs sustainable development has to target they could achieve this by exploiting collective efficiency, rural development with strategies that support the rural poor working in clusters, forming associations and engaging in extending benefits of development to them. subcontracting with large firms thus gaining from flexible specialization. Since the 1980s, African economies have endeavored to give micro interventions that have sought to create and promote the In this subsector study, the wood industry is used to examine development of enterprises or ease their constraints through the extent to which collective efficiency paradigm (Collective direct assistance in the field of finance, technology and skills efficiency refers to joint actions or collective efforts that are upgrading. Yet, the envisaged growth and transition, graduation made by enterprises working together, accessing the needed 75 International Journal of Business and Public Management (ISSN: 2223-6244) Vol. 1(1): 75-84 infrastructure jointly, to facilitate their individual enterprises The role of SMEs is well acknowledged in other countries such improved performance) is used in supporting the growth of the as Japan, Korea, and all other industrialized economies in terms wood enterprises and by extension SMEs. The use of the wood of creating employment, reducing poverty and increasing the industry is appropriate since forests are important renewable welfare of the society (Lukács, 2005). Lukács (2005) reports assets of a country’s wealth that even poor counties have all that SMEs and informal enterprises, accounted for over 60% of could posses. Forests provide renewable raw materials for a GDP and over 70% of total employment in low income wide range of industries with wood industries providing a wide countries, like Kenya. In much of the developing world, the range of products for consumption and intermediate purposes private economy is almost entirely comprised of SMEs and that thereby contributing to economic growth and development of a they are the only realistic employment opportunity for millions region or country. of poor people throughout the world. Lukács (2005) observes that there is little or no technological dynamism in this group, In Kenya, the performance of the wood industry has continued and few ‘graduate’ into large size or modern technologies. to decline over the years. As at 2009, virtually all large There is need therefore to investigate the extent to which sawmills had collapsed leading to the closure of Pan Africa collective efficiency is employed in planning and developing Paper Mills that was producing 80% of the pulp and paper infrastructure that in turn facilities the growth of SMEs. products in Kenya. Between 2001 and 2002, the wood and cork subsector performance dropped by 56% while import of timber 2.2 Infrastructure Planning and Development for Small increased from 78.2 m3 to 606 m3 in the same period (Kenya, Manufacturing Enterprises 2003). While the poor performance in the wood industry has Infrastructure and technology are a challenge for SMEs who been attributed to the ban of logging which in itself is a are hard put to accumulate capital hence can do little on manifestation of poor infrastructure planning, it is also their own to support infrastructure and technology indicative of the challenges faced in the growth of Small development. This calls for the adoption of the collective manufacturing enterprises within this sector. There is however, efficiency paradigm in the planning and development of insufficient literature on the use of networking and collective infrastructure in LDCs. Infrastructure offers supportive efficiency as a paradigm that informs infrastructure and structure for the growth of other sectors, raises growth of technology development that in turn support the growth of enterprises and reduce income inequity (Lopez,2004). SMEs in LDCs. Infrastructure planning and development, especially in rural 2.0 Literature review areas should support technology adoption and innovation 2.1 Small Manufacturing Enterprise that in turn lead to enterprises growth and building of Small-scale firms are significant and frequently a dominant competitive advantage. This does not seem to happen in component of the Industrial sector in most African countries LDCs where SMEs remain generations behind in the kind of (Liendholm and Mead, 1987). The micro enterprises (for technology they employ. This is one area where policy Kenya, small scale enterprises employing less than 10 pronouncements has not fully succeeded in creating a direct employees) account for the bulk of industrial employment in connection between infrastructure development, technology these countries (Liendholm and Mead, 1987). However, there acquisition, adoption and development and thus the growth are relatively few firms that employ 10 to 50 workers (small of individual SMEs. Research seems also to be treating this enterprises) and even fewer firms that employ between 50 and as separate and more so, not emphatically establishing 100 workers (Medium enterprises) in Kenya and hence they empirically the significance of the differences between the generate relatively little employment (Liendholm and Mead, inter-relationship from one region to the other, one country 1987). Given the dispersed settlement patterns in Africa, the to the other and one society to the next. emergence of rural towns as a focal point enables policy makers to provide the needed infrastructure for productive 2.3 Conceptual Models in Infrastructure Planning for Small small and medium enterprises at relatively lower costs. In Manufacturing Enterprises addition to roads or railroads, electricity and water, one must Since SMEs in LDCs are unable to develop infrastructure and not forget needed improvements in the institutional technology significantly on their own, then collective infrastructure such as developments of legal, information efficiency paradigm need inform the infrastructure planning systems and technology. These infrastructure-type and development so that SMEs engage in joint actions. The improvements are more important in low-income countries than thesis here is that this joint actions needs to be engineered in elsewhere. the planning and developing of industrial infrastructure, targeting to support SMEs access better or improved The contribution of small enterprises goes beyond employment technology and hence the growth of the individual enterprises generation. They also contribute to new innovation, and more and the sector as whole and its contribution to the importantly they engender entrepreneurial spirit. Indeed the industrialization process. promotion of small enterprises has become key element of government policy in many developing countries to stimulate The joint actions, as noted by Nadvi et al, (1994) works better economic growth and employment including self employment. when small manufacturing enterprises work/operate close As such many governments are actively supporting small together in clusters. Nadvi et al (1994) and Schimitz (1995) enterprise growth (Lukács, 2005). According to the statistics, in notes that industrial clusters are concerned with local growth industrialized countries, SMEs are major contributors to private processes that arise from sectoral and regional concentration of sector employment. Empirical studies have shown that SMEs small and medium sized firms that facilitates gain in efficiency contribute to over 55% of GDP and over 65% of total and flexibility. As pointed out by Schimitz (1995), the concept employment in high income countries. of collective efficiency is facilitated by the clustering on a 76 International Journal of Business and Public Management (ISSN: 2223-6244) Vol. 1(1): 75-84 number of subsequent development factors which include competitiveness. The technology acquisition and development Labour division; Specialization by SMEs; Rapid production of can only be facilitated by appropriate and relevant specialized products; Emergency of suppliers to handle raw infrastructure to be determined in a networking and collective materials, component parts and machinery; Emergency of approach. service providers such as technical, legal, communication among others; Emergency of marketing agents; Emergency of a In technology development, Gushesh (2003) indicates that pool of skilled workers and Formation of consortia or technology is accepted by society depending on the social associations for specific services and lobbying all of which context, the perceived ease of use and perceived usefulness in need to be considered in infrastructure planning and addressing society’s immediate needs. This means that society development. should be involved in determining what technology it needs and the direction along which it should be developed In infrastructure planning, Ombura (1997) points that (Constructivism). infrastructure networks are useful instruments within network economies. Infrastructure and related services help to make Traditionally, theories of technology have been informed by the things happen, it feeds and it is fed by trade, it fuels foreign determinist ideology which holds that the path for development direct investment, it backs up the creation and sustainability of is dictated by technical necessities and that pursuit for industrial clusters, it cuts costs and raises competitiveness. efficiency controls the direction of this path without any Infrastructure includes both hard and soft: ports Airports, reference to society (Feenberg, 1999). Critics to this ideology Railway systems, Road Networks Power, Communication, have argued that when choices are presented in the path of water, Waste management, IT, Legal, Financial and technological development, social influences play a vital role. Technological infrastructure (Ishikawa 2002). Constructivism puts forth an alternative ideology of technology development. According to Gushesh (2003) technical design is Infrastructure planning begins with industrial location choices influenced by society since human needs are seen to have which place spatial distribution of industry in reference to other cultural base. Thus cultures and societies would have different social aspects. A spatial planning approach ensures the most definitions of technology that would be appropriate to the efficient use of land by balancing competing demands within context of that society. That would explain why modern the context of sustainable development (Rozee, 2003). It technologies that have succeeded in developed countries fail in becomes an ongoing, enduring process of managing change by less developed countries and hence the need to engage local a range of actors, in the interests of sustainable development communities in participatory approaches when developing (Tewdwr, 2004). This makes efforts to promote industrial technologies appropriate to their context. development extremely urgent and rural focused. This study is informed by collective efficiency theory in SMEs A sustainable industrial policy and development strategies growth, networking and systems approach in infrastructure encompassing a variety of inter-related economic, social and planning and development and constructivism in technology environment objectives such as encouragement of an open and development. All paradigms encouraging stakeholders to come competitive economy, the creation of productive employment and work together for the betterment of their operations, and protection of the natural resources through efficient use of improved productivity and economic development of society renewable and non renewable resources required. Such a policy and leads to the conceptual model for the study figure 1. and strategy should create a self sustaining industrial sector having strong linkages with domestic economy. This, network 3.0 Research Methodology analysis approach in infrastructure planning portends that co- The study was an Ex Post Facto Subsector survey in three operative mechanism should be established alongside the categories of wood enterprises, sawmill; Panel production competitive rules of behaviour and take advantage of collective enterprises and furniture making enterprises in three districts, differentiation and learning (Ombura, 1997). It emphasizes Uasin Gishu; Kericho and Nakuru all in the Rift Valley pooling together to create infrastructure for use in network province of Kenya. The three study sites have the largest economies. This leads to the combined improvement in the proportion of wood industries in Kenya and have climatic fields of technology, marketing, transportation, communication, conditions favorable for both indigenous and exotic forest access to services and waste management with the benefit of covers. The districts also have fairly well developed social reduced costs in overcoming difference. This should work economic infrastructure with agriculture being the predominant together or in conjunction with the systems theory which source of income for the majority of the residents. The target requires that facility configuration be done in a distinctive but population was owner/managers of wood enterprises in the interrelated and inter dependent pattern (Catamase and Synder, three districts. For sampling purposes the administrative 1988). divisions in the three districts were used as sampling unit and the main shopping centers in each division sampled for data Small manufacturing enterprises represent such systems where collection. The sample size was determined to be 284 (3 panel interactions between infrastructure and technology determine production enterprises, 100 saw mills and 181 furniture enterprise development trends in a collective and networking producing enterprises) using the Krejcie et al, (1970) model. A environment. This brings to the fore the need for industrial multistage sampling strategy was adopted for the study. infrastructure planning and development that seeks to promote access to acquisition and development of technologies that lead Data was collected by use of a questionnaire containing both to improved efficiency, effectiveness and productivity of the open and closed ended questions, an observation checklist and small manufacturing enterprises. Thus, SMEs cannot attain a secondary data survey guide. Error variance minimization growth unless they employ technologies that allow for was considered at the research design stage and sampling 77 International Journal of Business and Public Management (ISSN: 2223-6244) Vol. 1(1): 75-84 employing the principle of triangulation where exclusive use 4.0 Study Findings of one method would bias or distort the picture of the particular 4.1 Background Information of the Respondents slice of reality under investigation (Cohen et al, 2000). The A sample of 284 wood enterprises was taken from three (3) content validity of data collection instruments were ascertained districts, Nakuru, Kericho, and Uasin Gishu, out of which 203 by peer examination of the instruments against stated study returned satisfactorily completed research instruments objectives and also by pre-testing the instrument. Consistency indicating a 71.5% return rate. The majority (74%) of the wood and replicability of the research instrument over time was enterprises are sole proprietorship which are mainly furniture established by the use of the test-retest method where ten (10) production enterprise followed by sawmills with very few respondents were selected from the neighboring Trans Nzoia panel production enterprises. There has been a steady increase district and the instrument administered twice with a two (2) in the number of wood enterprises with time with most started months intervening period. The test score were correlated between 2000 and 2006. The majority (71%) of the wood against the retest scores and a coefficient of correlation(r) of enterprises are aged between 1 and 10 years. The trend is the 0.931 obtained and a coefficient of determination (R2)=0.866 same in other developing countries where the majority of SMEs indicating strong instruments reliability. are less than 10 years (Bowen et al, 2009; Namibia, 2009; Fernando, 2003; Williams, 1997; Bala Subrahmantra et al, It should be noted however, that reliability cannot be assessed 2003). on a purely statistical basis and measures obtained in such studies are not the ultimate explanatory factors but merely The owner/managers were fairly youthful with a mean age of indicators of the presence of factors that cumulatively add up to 37.12 years with most (35.5%) aged between 31-40 years. This and are interpreted to construct the explanatory factors in form age statistics are similar to those observed elsewhere in of variable that are used in the analysis models (Cohen et al, developing countries (Bowen et al, 2009; Namibia, 2000; 2000). Dependability of data in this study has therefore been Kimuyu, 2001; Pogue, 2008; Bala Subrahmanya et al, 2003) achieved by respondents checks, debriefing by other scholars across the micro, small and medium enterprises in all industrial and peers, triangulation, prolonged engagement in the field, sectors. On gender, women participation in the wood industries repeat visits, persistent observation and studying industry sector is low (6.4%). This is a common trend especially in the records and data so that the study findings are consistent with manufacturing sector although women tend to dominate in the reality of the wood industry on the ground. trade (Institute of Economic Affairs, 2008; Kimuyu, 2001; William, 1997). In data analysis, codes were also used as scores. Care was taken to put into consideration the factors of theory (what is known Gender is said to affect enterprise performance in as far as their about possible responses), mutual exclusivity and relative strength is concerned. Kimuyu (2001) observed that exhaustiveness and details that should be factored into the male owned enterprise are at least twice as much in average coding decisions. Some variables were measured and coded by revenues compared to those in female owned enterprise. In the aggregation of measures for various sub-variables and also wood industries, however, the difference in performance is not aggregating scores for responses that are not mutually significant at the 95% confidence level with the male owned exclusive. Numeric data took the value of the numeral used as = the code for the response but care was taken to ensure that they enterprise having a mean 0.1771 and those female owned were in the same units. The study investigated and tested the enterprise with a mean = 0.1531 % of the wood enterprises hypothesis on the interrelationship between collective efficiency and the growth of wood enterprises. Each of these growth index. On marital status, the majority (84.7%) of the variables in turn depended on sub-variables as shown in the owner/managers are married with the respondents hesitant to development of the collective efficiency index (CEI) and the indicate the number of children and other dependants which infrastructure development index (IDI) under study findings. would be a measure of their family responsibilities. The null Hypothesis; Collective Efficiency does not play a 4.2 Collective Efficiency and the Infrastructure Development significant role in influencing infrastructure development in Accessed by Wood Enterprises wood enterprises in western Kenya. H0: IDI = f(CEI) thus, 4.2.1 Collective efficiency IDI=α+β (CEI) was tested in the study for linear, exponential The broad objective of this study was to investigate the and logarithmic relationships. The collective efficiency Index relationship between collective efficiency and the growth of (CEI) variable was synthesized from the respondents Wood enterprises in Kenya. The study sought to answer the involvement in collective efforts sub variables which included questions, to what extent is the collective efficiency employed Backward and forward linkage; Subcontracting; Sharing of in wood industries in Western Kenya? And test the null equipment; Networking and information sharing; Sector hypothesis that collective efficiency does not play a significant quality standards; Sector association; and Partnerships. A role in influencing the growth of the wood enterprises in measure of infrastructure development (IDI) accessed by wood Kenya. The collective efforts (joint action) enquired into products manufacturing enterprises in western Kenya was included subcontracting, sharing of equipment, networking, developed from sub-variables which include physical quality standards assurance, sector associations, backward and infrastructure consisting of roads, information, transport, forward linkages and partnerships. communication, water, energy, building and others like plant and access to other services such as banking, insurance and On subtracting, the most commonly employed effort is legal services that are important in facilitating industrial specializing in production of some parts and using others growth. bought in from neighbouring enterprises reported by 31% of the respondents followed by getting others to make some 78 International Journal of Business and Public Management (ISSN: 2223-6244) Vol. 1(1): 75-84 components for an enterprise (24.1%). These proportions are be developed to make a significant contribution to sustainable low. However, they show a significant effort towards industrial development. subcontracting but absence of a clear policy in support of subcontracting among SMEs is notable. On the sharing of tools In Kenya, the federation of Jua Kali Association is a national among wood enterprises, the most common practice is doing body with membership drawn from all districts Jua Kali work for neighbouring enterprise reported by 41% of the Associations, yet the wood enterprises owner/managers have respondents followed by borrowing/lending tools from and to not shown to be members. On the benefits from backwards and the neighbouring firms (15.8%); using neighbouring enterprises forward linkages in wood industries, the owner/managers do facilities to get some work done (11.3%); and getting not seem to be clear on them with the majority not responding neighbouring enterprises to provide services for the enterprise to the item on what they gain by linking to Agriculture, Trade, (7.9%). This shows a significant amount of equipment sharing. other industries and the service industry. Among those who Osinachi (2004) indicates that firms in Nigeria build a learning responded, most (28.1%) indicate they benefit from the network mainly to improve their performance through sharing Agriculture Industry since it buys their products, provide raw of tools, cost of transporting raw materials and information. materials (21.7%) and provide food (15.8%) for the wood industry sector. The most frequently mentioned area of information sharing is on quality (51.2%) followed by market (21%) then Technology The majority (51.7%) of the wood enterprise owner/managers and production methods in that order. The other areas of indicate that the trade sector provides market for the wood networking and cooperation mentioned by the respondent industry sector while other industries are seen to provide include delivery and expediting supplies (48.3%), sharing buildings and materials (3.9%), new technology (3.4%) and industry bulletin and report (21.2%) market information competition (3.4%) to the wood industry. The service industry (15.8%) and purchasing of materials (15.3%) among others. is said to provide education and health services (13.8%) and This suggests that deliberate efforts should be made to facilitate security 1.5% to the wood industry sector. Although these information sharing among SMEs, which again can be achieved proportions are low, they indicate a significant role played by through careful infrastructure planning and development with other sectors in the survival and growth of the wood industry the aim of bolstering this type of collective efforts and gains. In sector but more so, the lack of systematic efforts in support of Nigeria, the Chamber of Consumers and Industry provide backward and forward linkage between sectors and firms. business information for the firms and work with local Powers (2004) point out two ways an industry can be linked to manufacturers association to organize local trade fairs whose manufacturing, through purchases of manufactured inputs and effect (Osinachi, 2004). Bravtigarn (1997) notes that sharing of through sales of intermediaries to manufacturing firms. SMEs technical knowhow and skilled workers are benefits gained by gain from forward and backward linkages and there is need to small firms clustering in developing countries since individual support backward and forward links. firms cannot alone afford the cost of high technical skilled workers or invest in Capital goods. A Collective Efficiency Index (CEI) was synthesized from the joint actions discussed here. The Collective Efficiency Index On the question of wood enterprises cooperation in ensuring ranges from 0 to 1 in a continuum and the higher an enterprise product quality standards, it emerged that the most common ranks on the index the more the joint actions it engages in and collective effort is setting and adhering to certain quality the more it benefits from collective efficiency. It was observed standards in the sector reported (23.6%), collaborating in that the wood enterprises have a very low extent of use of joint pricing (21.2%) and checking each other quality performance actions with an index that ranges from 0.02 to 0.31 with a mean (19.2%). Yet, there are no structures on the ground to show that of 0.1029. The majority (99.5%) of the wood enterprises were this takes place as a deliberate collective effort in Kenya. grouped into very low (0-0.25 CEI) collective efficiency Producers turn to export markets when local markets are quartile as shown in figure 2. This shows that the wood saturated (Cawthorne, 1995) and quality standards determine enterprises participate in minimal collective efforts. the export drive for clusters (Nadvi, 1999). What this portends for the wood industries in developing countries is that, not only The absence of systematic structures and infrastructure that is it threatened by failure to meet quality standards for the facilitate collective efforts could possibly explain this and is a export market but even the local market will be lost to imports pointer to a direction for intervention in infrastructure planning due to better quality and lower prices as a result of better and development. This raises the question, is there sufficient technology that results in efficiencies and lower production evidence that the collective efforts undertaken, however costs. Consequently, SMEs have to shift focus to verifying the minimal, benefit wood enterprises? Does the collective quality control process and the quality values installed in each efficiency have any influence what so ever in the growth and enterprise at every stage of the production process as noted development of the wood industry? An analysis of Variance (Nadvi, 1999; Kaplinsky and Readman, 2001). indicate that there is no significant difference in the level of collective efforts across the various sub sectors of the wood Participation in wood industries sector association is low with industry, (F=0.168, P=0.820, α=0.05) but the difference the highest frequently mentioned (9.9%) indicating they between the means is significant (F=3.583, P=0.030, α=0.168, participate in industry annual parties, 3% join and contribute x=0.05) when examined by location (study districts) with towards common market especially export market, 2.5% Kericho significantly worse off. The lessons here are that participate in common annual exhibition while only 2% of the collective efficiency woul play a significant role in buttressing respondents are members of sector/industry association. This SMEs growth and needs to be considered when planning low performance in a collective efficiency measure indicates an infrastructure for industrial development. area that has to be pursued relentlessly if the SMEs sector is to 79 International Journal of Business and Public Management (ISSN: 2223-6244) Vol. 1(1): 75-84 4.2.2 Infrastructure Development Accessed by Wood 72.9% do not access public transport, they rely on other means. Enterprises in Kenya It is also worth noting that while it would be desirable for Infrastructure is expected to influence the industrial sector. SMEs to access a multiplicity of means of transport so that they Physical infrastructure-roads, information, transport, choose on the basis of cost, no single means is accessed by communication, water, energy and buildings were examined in more than 27.1% of the respondents. Poor transportation limits wood industries. In addition, the plant and other services access to raw materials and markets and affects production accessed were examined. The location of wood enterprises cost. According to Brojonegor (2009), existence of reliable and from rural and urban point of view was noted to be mainly sufficient electricity, energy, water supply, good and reliable urban centers (77.3%) with an indication that they are on information communication technology systems, enhancement average 12.4 km from a major town centre and 1.5 km from the of production capacity would bolster the performance of SMEs. nearest similar industry. The finding is similar to those of The study revealed a poor road network with only 34.5% of the Kimuyu (2001) and Pogue (2003) who noted that more than respondents accessing tar marked roads which are on average half of businesses are located in urban centers. Locating small 1.34 km from the enterprise. Poor road networks for removal of enterprises in town centers influence its performance in that it forest products are noted in Romania (Cretu, 1996) among accesses better infrastructure, is closer to its potential other less developed and developing countries, a challenge that customers and accesses a pool of better skilled labour from has to be continually addressed in infrastructure planning. youths who migrate to town in search of better wage jobs. Alternatives to roads such as railway, ropeways combined with According to Kimuyu (2001), location mops up performance roads have been developed and used in Central Switzerland effects of spatial differences in the business environment such (Durhstein, 1996) indicating need to explore alternatives in as marginal differences in the state of the infrastructure and Kenya. their imperatives. The most common means of communication is mobile On the site/ plot ownership, it emerged that the majority telephone used by 95.1% of the respondents. Internet and fax (79.3%) of the respondent do not own the premises where they have low usage, 10.3% and 4.4%, respectively by wood operate from. This indicates that the majority of wood enterprises. The majority 78% of the respondents do not access enterprises owners have no ability to accumulate capital to industrial information with only 1% obtaining information enable them buy their business premises. Other studies have from the Ministry of Trade. The problem of inadequate similar findings (William, 1997 and Kimuyu, 2001) suggesting communication infrastructure and skills has been noted in other unstable business environment and negative effect on growth sectors in Kenya (Bowen et al, 2003; Kashorda, 2007) and in potential. The problem is more or less the same across the Sri Lanka (Fernando, 2003). Yet, the importance of adequate study sites and type of wood industry. The enterprises are also and efficient communication cannot be overstated. Moodley handicapped in that they cannot use their insecure business (2002) notes that the structure of industry and market requires premises as collateral to obtain credit for enterprise growth. On adoption of ICTs and the government policy and support in the source of industrial energy, the majority (42.9%) use promoting internet-based communication are expected. The electricity with a significant 16.7% and 3.9% using generator wood industry sector would benefit significantly from adoption and fuel wood respectively. Electricity is also the main source of Information Communication Technology in order to of lighting with the lamps and generators used by a significant facilitate its integration into the global furniture value chain proportion 18.7% and 11.5% respectively. UNIDO (2007) (Moodley, 2002). observes that local availability of energy resources determine their use. Incidentally, solar energy has not been exploited with The productive assets employed by wood enterprises are an only (2.0%) of the respondents indicating they use it, yet Kenya important aspect of industrial infrastructure. Most (46.3%) of has an abundance of sun most of the time and wind which is the respondents use temporary structures, 21.7% use semi not reported to be used at all. permanent while 16.7% use permanent structures. A comparison of the wood enterprise performance using a one It has been recommended that there is need to design way analysis of variance shows that the variance between appropriate technology package linking local resources and means is significant (F=3.90, P= 0.004, α=0.005) indicating creating awareness about the potential economic benefits of that the wood enterprises operating in semi permanent applications of renewable energy and taking an integrated and program approach that would enhance successful adoption of structures perform significantly better (n= 46, =0.23) than industrial application of renewable energy in SMEs in Africa those in permanent structures (n =33, =0.17) and the least (Monga, 2007). Water is a major challenge in less developed countries with only 31.5% of the wood enterprises in western performing being those in temporary structures (n=94, Kenya accessing piped water while the others use rivers/dams, =0.1365). This vindicates Kimuyu’s (2001) observation that wells/boreholes, and rainwater. It was observed that in Vietnam businesses that operate in temporary premises are subject to most paper mills use river water (Rudolf, 2003), while in disruptions and distortions of productivity and continuity that Kenya 75% of small manufacturing enterprises in general do affects their enterprise performance. not access water at all. This is a challenge that should be addressed in infrastructure planning and development for sustainable growth of SMEs leading to sustainable industrial The wood enterprises use mainly manual cleaning (96%) with development. low stock holding averaging between Kshs. 1,000 and 5,000 of raw materials held by (25%) of the respondents, working in On means of transport, most (27.1%) of the respondents use progress of between 1,000 and 5,000 held by 24.6% and public transport but the opposite is the most informative, that finished goods of between Kshs. 1,000 and 5,000 held by 80 International Journal of Business and Public Management (ISSN: 2223-6244) Vol. 1(1): 75-84 (20.2%) of the enterprise. This challenge of low investment has accessed and used by wood enterprises. The question, is there a been noted elsewhere. Kenya (1999) noted that many of the relationship between infrastructure and collective efficiency in wood industry firms in Kenya belong to the small or informal wood industries? And what is the nature of the relationship?, sector with the smallest sawmill handling 500 cubic meters of are tackled under this section. wood annually. AKE (2008) indicates that in Finland, 60% of the wood enterprises are small, owning only one machine. In The variables Collective Efficiency Index (CEI) the dependent Russia, Turpenen (2008) points out that sawn timber was variable and the infrastructure development index (IDI) are produced primarily utilizing worn out and outdated equipment examined for linear, exponential and logarithmic relationships. with Low Level Automation. In Romania, there are no proper A Summary of Analysis of the parameter estimates of material buffer in front and behind each machine with incorrect Relationship between Infrastructure Development Index (IDI) dust removal (Budeu et al, 2009) while in Nepal, the main and Collective Efficiency (CEI) are shown in table 1. This equipment in the set include axe, saw, sharpener, and hammer shows that the relationship between Infrastructure (Acharya and Acharya, 2007). These findings suggest that Development and Collective efficiency is linear since r=0.305 SMEs should be facilitated to acquire better, secure, and larger and R2 =0.093 for the linear function are higher than those of workshops that facilitate operations of the modern equipment log linear; exponential and logarithmic functions. This implies and the nature of wood working enterprises. that Infrastructure affects collective efforts in wood enterprises linearly and that there is need to deliberately develop The other services accessed by wood enterprises is Banking infrastructure with a focus to supporting joint actions and (86.2%), legal (65%), credit (21.7%) and Insurance (2.0%). collective efforts in wood enterprises in particular and the small The banking services are accessed on average 16.34 Km from manufacturing enterprises in general. This would in turn the wood enterprises while those who access legal services contribute significantly to sustainable industrial development. have to travel on average 5.2 km to access it. Williams (1997) sees difficulty in securing credit as the greatest problem for 5.0 Conclusion SME development while Fernando (2003) says SMEs do not Collective efficiency, the competitive advantage SMEs derives borrow from banks because of bureaucratic procedures and from external economies and joint actions in wood enterprises burdensome collateral. In Namibia, 50 % of SME do not apply in Kenya is low. The majority of the wood enterprises are in the for loans (Namibia, 2000). Lewis et al (2004) asserts that lack 1st quartile of the collective efficiency index and there is no of credit leads to SMEs continued use of outdated equipment significant difference across the subsectors of the wood that causes inefficiency. What this means is that left on their industry. While the variances between the means of the CEI by own, SMEs have no means or capability to extricate them from the study districts are significant, all the parameters (indicators) this vicious circle. On the whole, Infrastructure as it relates to of collective efficiency indicate low performance in the extent provision of access roads, adequate power, water, sewerage and of use of joint actions. The infrastructure accessed by wood telecommunication has been a major constraint in the industries in western Kenya is poor. development of SMEs and should be critically evaluated when planning infrastructure for SMEs growth. The infrastructure development index is on average low with majority accessing infrastructure classified as low and very low When all the above discussed measures of infrastructure (1st and 2nd quartiles of the Infrastructure Development Index. development are pooled together in computing an Infrastructure Uasin Gishu district has better infrastructure compared to Development Index (IDI), a continuum ranging from 0 to 1, it Nakuru and Kericho while there is no difference in is noted that the IDI score for each wood enterprise ranges from infrastructure accessed between different wood industry 0.04 to 0.71 with a mean of 0.324 and 76.5% of the wood subsectors. The relationship between infrastructure and enterprises below 0.5 as shown in the scatter plot figure 3 and collective efficiency is essentially linear. This means that better suggests a lot of efforts are needed in infrastructure planning Infrastructure will always lead to better and more efficient joint and development to ensure wood enterprises access well actions and benefits from them. For the Small Manufacturing developed infrastructure. Comparing infrastructure access in Enterprises (SMEs) to play a significant role in the the three study districts, it was observed that there is a Industrialization process, infrastructure planning and significant difference in the levels of infrastructure accessed development has to be informed by the SMEs potential in the but not significant across types of wood industry. On the industrialization process and the challenges they encounter that whole, the type and level of access to infrastructure essential hinder the individual enterprises growth and that of the SME for a manufacturing enterprise is generally poor and low. FAO sector collectively. (1997) noted that infrastructure development remained low while demand and consumption for forest products increased Specifically, the study recommends that; with population growth. (i) Planning for sustainable industrial development should shift focus to the Local Small Manufacturing 4.2.3: The Relationship between Collective Efficiency index Enterprises (The Jua Kali Sector). (CEI) and Infrastructure Development index (IDI) (ii) Collective efficiency, Networking, Systems approach Infrastructure plays a key role in the growth of the economy, and constructivism should be used as the basis for the growth of the country and supports the growth of all planning and developing infrastructure and sectors. Infrastructure provides vital links for easier technology for sustainable industrial development. dissemination of information that facilitates commercial (iii) In order, to anchor SMEs as a vehicle towards exchange. 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