The scale of entrepreneurial ecosystems (EE) assesses the perceptions about entrepreneurial ecosystem domains, finances, capital finances, support, support professions, policies, markets, human resources, and culture. The scales are always error-prone—these scales must possess properties that enable them it to provide maximum information and validity reliability. Convenient sampling data from (n = 474) founders, co-founders, and entrepreneurs were collected. The IRT-GRM model is used to validate and test the instrument-based on polytomous scales. IRT yields discriminating power—the level of difficulty of the items of the scale. The scale consists of 48 items. The item Pol5 (4.13) was found to have the highest discriminating value (4.13), the item mar5 had the lowest discriminating value (1.57), and all items had discriminating values greater than the threshold value of 0.60. The EE Scale showed good reliability based on McDonald’s omega and Cronbach’s alpha (0.80 and 0.88). The parallel and factor analysis showed good agreement of the one-dimesnionality of the scale. The model goodness of fit statistics based on the comparative fit index (CFI) and the Tucker–Lewis index, (TLI) and the standardized root mean square residual (SRMR) showed a satisfactory level of fit; however, the root mean square error of approximation (RMSE) showed a poor fit. The item characteristic curves showed that the all item responses were properly ordered. The items of the scale showed a satisfactory level of discrimination power and level of difficulty, and it was found to have three levels of agreement about entrepreneurial ecosystem scale. It is concluded that the EE scale possesses good psychometric properties and that it is reliable and valid instrument to measure the entrepreneurial ecosystem of the given region.

The role of non-academic staff in ensuring the effectiveness, efficiency, and smooth functioning of Higher Education Institutions has become increasingly significant, particularly within the context of developing countries like Pakistan. However, in public sector HEIs, the focus on building the capacities of non-academic personnel remains minimal compared to academic staff development initiatives. This qualitative study investigates the current state of capacity building mechanisms for non-academic staff in public sector HEIs of Pakistan, highlighting challenges, existing gaps, and potential strategies. Through in-depth semi-structured interviews with ten non-academic staff members across five major universities, the study employs thematic analysis to identify key themes influencing staff development. The findings reveal systemic neglect, absence of structured training programs, limited career progression pathways, and insufficient institutional commitment. Drawing on best practices and relevant theoretical frameworks, the study proposes a comprehensive model for capacity building aimed at enhancing administrative efficiency, service delivery, and institutional governance. The paper concludes with recommendations for policymakers, higher education administrators, and human resource departments.

Sindh’s clean energy transition reflects a complex interplay of social readiness, technical capacity, and institutional coherence. Despite Sindh’s strong renewable potential, averaging 5.8 kWh/m²/day of solar irradiance, progress remains constrained by governance failures, financial limitations, and coordination gaps. This study evaluates the drivers and barriers shaping clean energy initiatives (CEIs) in Sindh using an integrated Force Field Analysis (FFA) and Multi-Level Perspective (MLP). Primary data were collected from 35 semi-structured stakeholder interviews conducted in Hala (Matiari) and Khairpur Districts, supported by provincial policy documents and secondary literature. The results identify 30 major forces: 11 enablers and 19 barriers operating across social (niche), technical (regime), and political-economic (landscape) levels. Social participation and women-led enterprises emerged as key enablers, whereas low technical literacy, fragmented institutions, and weak financing systems persisted as dominant constraints. The force field analysis score (ΔF = -67.1) indicates a negative transition momentum, suggesting that Sindh’s clean-energy transformation is socially emergent but structurally constrained. Theoretically, the study advances transition research by operationalising the MLP through quantitative force weighting, offering a diagnostic framework to assess transition fragility in developing-country contexts. Practically, it underscores the need for governance coherence, financial innovation, and community-based energy literacy to transform scattered pilot projects into resilient, inclusive renewable energy systems.

The Defined Benefit (DB) pension system operates under a Pay-As-You-Go (PAYG) framework, providing guaranteed post-retirement income and family pension benefits to Government Employees worldwide. However, rising pension liabilities, demographic shifts, and limited fiscal space have rendered the system financially unsustainable. Pakistan is not out of this problem, and Higher Education Institutions (HEIs) are particularly affected, as an increasing proportion of their recurrent grants is diverted toward pension obligations, constraining academic and developmental activities. While global pension reforms are well documented, the perspectives of operational pension administrators within Pakistan's HEIs remain largely unexplored. This study investigates sustainable reforms to optimise the DB pension payment system in HEIs. A qualitative multiple-case study design was used, including in-depth interviews with directors of finance, pension officers, auditors, and members of the HEC Board of Governors (BoG), supported by an extensive literature review. Using thematic analysis, both pre-empirical (literature-driven) and post-empirical (field-driven) frameworks were developed, identifying 25 additional mechanisms for controlling pension payments. The study proposes a comprehensive, evidence-based framework to assist policymakers, HEIs, and governing authorities in strengthening the financial sustainability of the DB pension system while ensuring the welfare of current and future employees.