The commencement of China–Pakistan Economic Corridor has led to the appreciation of Pakistan’s economic outlook from 5.4% to 5.8% by the World Bank. The upgraded outlook is a welcome sign but it is still trivial, essentially attributable to the electric power crisis, which approximately trims 2% of Pakistan’s economic growth annually. Almost 60% of the CPEC (China–Pakistan Economic Corridor) funds are directed at Pakistan’s energy sector, hence, demanding careful attention of both researchers and policy analysts alike. The study is based upon a meta-analytic review of literature concerning CPEC and Pakistan’s energy sector. The results of the study demonstrate that CPEC is an easing agent for Pakistan’s energy crisis (82.30%). The results also highlight points of concern, including inadequate planning (47%), dilapidated electricity distribution system causing losses (64.7%), and an unsustainable energy mix (64.7%). The study further validates the findings via Spearman’s Rho-Correlation. The rρ value for the possible “resolution of Pakistan’s energy crisis” is 0.5426 achieving a significance level of 98% and a corresponding p-value of 0.0252. The significant negative rρ value attained is −0.4894 which establishes the fact that lack of planning can hinder the energy crisis resolution.

Purpose: This paper not only draws conclusions from the available literature but also offers some new factors as well, which are not included in the existing literature. To be more precise, the purpose of this paper is to ascertain factors behind the clustering of the motorcycle industry, a low-tech and low investment industry. This paper weighs the government’s policies, role of factors of production, infrastructure, geography and other drivers for the subject industry and associated industries in the geographic location of Hyderabad. Design/methodology/approach: For collection of data, a questionnaire was designed to survey the cluster (n=250) after reviewing the literature and conducting interviews of experts of the motorcycle manufacturing industry, i.e. owners, managers, auditors, suppliers, etc.; a component matrix was developed to reduce the dimension of factors and measure the correlation, which helped to weigh the influence of factors. A confirmatory factor analysis proposed four factors as the best fit. Findings: The study conjectured a new viable factor for industrial clustering: “ethnic community,” as it acts as a catalyst to diffuse knowledge, experience and skills within the industrial cluster. Research limitations/implications: This research does not find the weightage of the factors for industrial clustering, i.e. it does not calculate the influence of factors behind the industrial clustering. Practical implications: The above findings aim to stimulate policy makers and researchers alike to further pursue the line of inquiry developed in this paper. Originality/value: A first-time confirmatory factor analysis is used to find the reasons of industrial clustering. Root mean square error of approximation is used to test the model fit. Most importantly, it is the research about an emerging industrial cluster.