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Renewable energy adoption decisions in Jordan's industrial sector: Statistical analysis with unobserved heterogeneity

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  • Hamed, Mohammad M.
  • Mohammed, Ali
  • Olabi, Abdul Ghani

Abstract

This paper models two strategic decisions made by industrial entities: the intention to adopt a renewable energy system (RES) and the timeframe for this adoption. The methodology presented considers multiple layers of “unobserved heterogeneity.” The results of random parameters imply that the parameters exhibit unobserved heterogeneity across industrial entities. For example, high non-electric energy costs increase the probability of selecting a shorter timeframe in 81.8% of entities and reduce that probability in 18.2% of entities. The results of this study also show that the majority (60%) of responding entities intend to adopt an RES within a short timeframe, generally one to two years, while 40% intend to adopt an RES three or more years after 2022. According to our findings, green bank loans, electricity tariffs, the type of industry, government bureaucracy, and entities’ export capabilities predominantly influence their intention to adopt an RES. The results also show that energy-intensiveness (e.g., industrial entities in the plastic and rubber, food and drinks, and chemicals and paints sectors), high electricity tariffs, and elevated non-electric energy costs often expedite the adoption process (resulting in shorter adoption timeframes). Government impediments tend to cause entities to delay their adoption decisions. Capital costs are by far the largest impediment to adoption, as indicated by 29.3% of the surveyed entities, followed by government legislation at 18.6%. The findings presented offer crucial knowledge for creating opportunities to implement new policies and produce an environment in which industries can expedite their transitions to renewable energy.

Suggested Citation

  • Hamed, Mohammad M. & Mohammed, Ali & Olabi, Abdul Ghani, 2023. "Renewable energy adoption decisions in Jordan's industrial sector: Statistical analysis with unobserved heterogeneity," Renewable and Sustainable Energy Reviews, Elsevier, vol. 184(C).
  • Handle: RePEc:eee:rensus:v:184:y:2023:i:c:s1364032123004252
    DOI: 10.1016/j.rser.2023.113568
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