Heliyon (Jan 2024)

The predictors of social capital in agricultural consultation, technical, and engineering service companies

  • Pouria Ataei,
  • Afshin Mottaghi Dastenaei,
  • Nasim Izadi,
  • Hamid Karimi,
  • Meysam Menatizadeh

Journal volume & issue
Vol. 10, no. 1
p. e23853

Abstract

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Social capital is an essential type of capital that influences the growth and development of societies. The present descriptive-survey research aimed to capture CEOs' social capital predictors in the agricultural consultation, technical, and engineering service companies in Fars province, Iran. The CEOs, who amounted to 107 people, all participated in the research. The data collection instrument was a questionnaire whose content and face validity were confirmed by a panel of experts and whose reliability was calculated by Cronbach's alpha at 0.82. Data were analyzed in the SPSS22 software package. Based on data analysis, eight social capital items were derived and prioritized. They included social participation, social proactivity, social trust, neighborhood connections, friends and family connections, capacity to accept differences, appreciation of life, and work connections. Based on the ranking of these elements, social proactivity, work connections, and friends and family connections were ranked first to third, respectively. Also, step-by-step multiple regression analysis revealed that the three variables of the feeling of job security, investment, and media were the independent variables that accounted for the CEO's social capital. Programs provided by the media should focus on promoting people's social solidarity. Some investment must be made by these companies in social activities and encouragement of the target community's participation and trust. The success of the agricultural consultation, technical, and engineering service companies is based on the principles of specialty, trust, participation, and social solidarity, showing the existence of social capital in these companies. Therefore, social capital and factors that predict it influence the productivity and efficiency of the companies.

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