Characteristics and determinants of success of cooperatives in the Philippines

• Main Author: Dapun, Lope E.
• Format: text
• Language: English
• Published: Animo Repository 2002
• Subjects: Cooperative societies; Success in business; Business Administration, Management, and Operations
• Online Access: https://animorepository.dlsu.edu.ph/etd_doctoral/913
• Institution: De La Salle University

This study examines the factors which contribute to the success of cooperatives in the Philippines. The study made use of two groups of cooperatives. One hundred twenty-seven (127) cooperatives awarded as Outstanding Cooperative by the Cooperative Development Authority (CDA), Department of Agriculture (DA) and Land Bank of the Philippines (LBP) in its nationwide Annual Search for Outstanding Cooperatives from 1994 to the present comprised the successful cooperatives group. These outstanding cooperatives were matched with non-successful cooperatives group based on geographical location, type of coop and asset size. It is emphasized that under this definition, being not successful does not mean cooperative failure but referring to the status of coops that are active or operating and striving to exist. From cooperative literatures, the non-financial and financial factors as predictors of success, was conceptualized. The non-financial factors, grouped into organizational, economic and management, basically depict the qualitative and quantitative aspects of business operation while the financial factors include financial ratios depicting financial performance and status. A specifically designed questionnaire was used in the collection of data pertaining to the cooperatives. The study aimed to have a profile of the successful cooperatives in terms of non-financial and financial factors. These factors that significantly predict cooperative success were determined through the development of models using logit and factor analysis. Results of the study showed that as business organizations, cooperatives have their distinct strengths and weaknesses. Cooperatives consider the attributes regarding operation, capitalization and members, more as a strength than a weakness. Cooperatives are likewise saddled with difficulties/problems in the course of operation but differs as to the degree of difficulty and the length of time or period experienced. Collecting receivables served as the perennial difficulty experienced by all the cooperatives. Looking at the financial characteristics of the cooperatives, results further showed that the outstanding coops exhibited better financial performance figures compared to the non-outstanding coops. The survey results paved the way to the development of six models of predictors of cooperative success. The accuracy rate of the models to predict a cooperative as being successful or not varies from model to model between 59.3 percent to 67.8 percent. As a consequence of these models, three factors were found to discriminate between sucessful and non-successful cooperatives. The generic model shows that cooperatives with highly or more integrated type of business activities have greater chances or propensity to be successful. Likewise, coops that avail the services of professional advisors or experts are found to have greater chances of being successful. Finally, coops that maintain industry or generally accepted average liquidity level have higher propensity to be successful. Corollary to the logit models, using factor analysis, eight dimensions or variates were found to characterize the outstanding or successful cooperatives as depicted in the factor solution. As its core characteristic, successful cooperatives are run by people with strong leadership, coupled with competent management, maintain sound communication practices as its nexus with members, with clear focus of mission, objectives and integrated activities. These factors are inferred to contribute to the strong commitment of members to the cooperative. Considering that there are factors not captured in the developed models, it is emphasized that the models are not meant to replace existing decision-making techniques. The models are to be used in conjunction or complementation with existing techniques to improve decision-making.