Each industry is continuously doing self appraisal and in search of tools for measuring its present performance in comparison with the set goals, past achievements, and capacity   utilization.   Policy   formulation   and   business decision making depend on economic indicators. Manufacturing capacity utilization is an important indicator of economic performance that explains changes in     inflation, investment,  long run  output    growth (Sarbapriya, 2013). Capacity is very important but least understood concept in manufacturing and business world (Klammer, 1996). Different categories of people in business and manufacturing measure capacity differently. For example, some financial managers might measure plant capacity in terms of the equipment installed in the plant while operational supervisors might measure capacity in terms of worker efficiency. Klein and Summers (1996) defined an organization’s productive capacity as “the total level of output or production that it could produce in a given time period”. Capacity utilization is the percentage of the firm’s total possible production capacity that is being used. Therefore, an organization should be most efficient if it is running at 100% capacity utilization. An organization’s full capacity is the minimum point on total cost function, a full input point on the aggregate production function and a bottleneck point in a general equilibrium system. Full capacity should be defined as a realizable level of output that can be attained under normal input conditions without prolonging accepted working schedules, and allowing for usual vacations and for normal maintenance (Klein and Summers, 1996).

To positively affect inventory levels, cycle time, business processes, and customer service, modern Supply Chain Management (SCM) should reduce their constraints hence leading to increased firm profitability and competitiveness. According to Russom (2000) and Handfield and Nichols (2003), efficient, effective supply chains are critical to the survival of most organizations. Supply chain management, therefore, is a current research area for business management worth a study. This study tested whether the firm’s capacity utilization had practical implications on the firm’s value chain performance.A typical supply chain frequently involves three segments made up of the upstream segment, internal supply chain, and downstream segment. The upstream supply chain segment is where sourcing or procurement of materials from external suppliers occurs; internal supply chain segment is where transformation (operations), assembly, and packaging take place; and downstream supply chain segment is where distribution to customers takes place, frequently by external distributors, or a disposal takes place (Sandoe et al., 2001; Handfield and Nichols, 2003). Most studies (Russom, 2000; Drickhamer, 2002; Donovan, 2003; Chopra and Meindl, 2004) have in the past focused on the whole supply chain performance, failing to focus on performance measures for specific segments of the supply chain particularly the internal chain. This study will focus on the firm’s internal supply chain segment analysis which can be easily related to the firm’s capacity utilization and the firm’s internal operational constraints. Based on the studies of Russom (2000), Drickhamer (2002) and Donovan (2003), this position is supported by the Supply-Chain Operations Reference (SCOR), which divides supply chain operations into various parts giving suppliers,   manufacturers,   distributors,   and  retailers  a framework within which to evaluate the effectiveness of their activities along the same supply chains.

This study was grounded on Theory of Constraints (TOC) and the Resource Based View (RBV) theories which have played an important role in Supply Chain Management research (Grimm, 2004). The key theoretical perspectives that have been greatly used in supply chain management studies in the last twenty years are the TOC and RBV (Alain and Martin, 2009).

There are two approaches to measuring capacity utilization. The first approach measures capacity utilization using an estimated cost function. Another approach uses Federal Resource Board (FRB) or Wharton measure that investigates the macroeconomic implications of high or low capacity utilization. Sarbapriya, (2013) observed that very little research work has been undertaken on economic measurement of capacity utilization since most of the studies on capacity utilization had used conventional methods and had paid less attention to the possible theoretical problems. Therefore, there was a need to have a study to extend the concept of capacity utilization beyond conventional methods and build up some new theory.

Kenya is currently the world’s third largest producer of tea after India and China but the leading exporter of black tea. Kenya’s tea industry is well developed and contributes about 20% of the Kenya’s total export earnings. Since 2009, the Tea industry has been the highest foreign exchange earner generating Kshs 92 billion in 2010. The major markets for Kenya's tea include Pakistan, Egypt, United Kingdom, Afghanistan, Sudan, Russia Federation and Yemen. Kenya’s tea exports mainly constitute of black CTC (crush tear and curl) teas in bulk and exports of green teas are still very low (http://epckenya.org).

Problem of research and research focus

Tea processing involves value addition as opposed to manufacturing. The concept of the value chain and capacity utilization fit well into the context of tea processing, but most studies have had a mismatch between the concept of capacity utilization and value chain management. Guy et al. (2005) did a study on impact of application of TOC in the health sector and found out that the number of patients in outpatient increased but there was no actual value addition, the reason might have been on issues to do with capacity. These findings further contradicted by Inman et al. (2009) who indicated that setup time reduction would have little effect on overall firm performance unless the setup time of a constraint was reduced. Choosing the tea processing as the context of value chain performance is a strong strength as the proper understanding of the local measurement of the firm’s value chain performance can lead   to   global   supply    chain    performance     of   the organization. This study tested the TOC philosophy that local performance does not necessarily translate to global performance. This study was conducted in the form of a survey covering the whole of Kenya in an effort to clear the contradicting TOC philosophy on performance using cross sectional survey.

Capacity is the maximum level of output each plant in a given industry can achieve within the normal work schedule, considering the normal downtime and assuming that sufficient inputs to operate machinery and equipment are availability (Corrado and Mattey, 1997). According to Saikia (2012), simple indicators like the output gap based on designed capacity are used to measure capacity utilization. This direct measure of capacity output has limited use since it overlooks problems such as seasonal grown up of certain proportions; expansion capacity due to fresh investment. Capacity utilization is a measure of the firm’s productive capacity that influences the total level of output or production that could be produced in a given time period.

Another approach for defining capacity is developed by Consortium for Advanced Manufacturing International (CAM-I) which categorizes the capacity into three (productive, nonproductive, and idle) and uses the term “rated capacity” instead of the term “theoretical capacity” in its model. Rated capacity is equal to the sum of the idle, nonproductive, and productive capacity in the CAM-I model (Klammer, 1996). Capacity or plant capacity is the maximum rate of output that a plant can produce under a given set of assumed operating conditions (Stratton, 1996). Capacity of the plant includes all the facilities, equipment, and people used to make the product and the ways those facilities, equipment, and people are used. It is a measure of a manufacturing enterprise's ability to provide products to its customers when needed or a manufacturer's ability to meet demand (Stratton, 1996). Effectively managing capacity can help organizations to create a competitive advantage which is very crucial for the survival of those organizations. The purpose of managing capacity is to ensure that organizations provide the cost-justifiable resources needed to meet current and future business requirements.

Market constraints as a result of market demand lead to a reduction in capacity utilization in the organization. Market price changes have become so prevalent in today’s business environment than the past situation making it difficult for organizations to manage their value chain activities. Various commodities like agricultural products, metals, and energy often experience significant and unexpected price fluctuations that have a direct financial effect on profitability, organizational cash flow and competitiveness (Zsidisin and Hartley, 2012). Falling commodity price changes force organizations to change their production levels in response to lower prices hence leading to idle capacity in organizations. Increasing commodity prices will force organizations to enhance their produce so as to benefit from the price increase. Price fluctuations if not well managed will lead  to  delays, request for price increases, supply disruptions that detrimentally affect the overall cost structures and sourcing options (Zsidisin and Hartley, 2012).

Shepherd and Günter, (2006) argued that performance measurement should measure supply chain relationships in the entire supply chain rather than measuring intra organizational performance only. Supply chain performance measurement should complement human resource management and modern manufacturing practices (Shepherd and Gunter, 2006). Performance measurement system should be dynamic by responding to environmental and strategic changes in the organization. Organization’s performance should based on the financial measures, the internal business process, the customer satisfaction, and the learning and growth aspects (balanced scorecard- BSC) (Kaplan and Norton, 1992, Bhagwat and Sharma, 2007b). 

As a result, the main knowledge contributions (theoretical and practitioner) from this research stems from the concurrent treatment, in the same study, of an expanded approach tocapacity utilization and value chain performance within a key sector meant to deliver Kenya’s vision into a developed economy.Even though the concepts of capacity utilization and value chain performance have been widely researched, a few studies have tried to study the trends and determinants of capacity utilization and value chain performance of organizations. Further, much prior scholarly discourse has studied the concepts of capacity utilization and value chain performance in isolation and no attempt has been made to study the two variables together; this leaves plausible research opportunities in this area to bridge the gap. Consequently, the study sought to determine the relationship between capacity utilization and value chain performance of tea processing firms in Kenya.The study sought to answer the question: Is there arelationship between capacity utilization and value chain performance of tea processing firms in Kenya?[1]  The specific research objective of this study was to determine the relationship between capacity utilization and value chain performance of tea processing firms in Kenya.

The model provided in Figure 1 is emphasizing the inter-connection between capacity utilization and value chain performance in one comprehensive framework  intended to aid the researcher in developing a more thorough understanding of the linkages between the above two concepts. The hypothesized relationship shows capacity utilization is the independent variable while value chain performance is the dependent variable. Capacity utilize-tion was hypothesized in terms of design capacity and actual output while value chain performance was hypothesized in terms of financial performance, customers’ satisfaction, internal business process, and organizational capacity utilization.

Based on the study objective, the following hypothesis was tested:

H_o: There is no relationship between capacity utilization and value chain performance of tea processing firms in Kenya.