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Nowadays, informed decision-making is catching up. Technological advancements and computing ability further fuel and facilitate this tilt toward informed decision-making. In such a scenario, data is cynosure. Therefore, the ability to gather data by a nation (incredibly accurate public data) becomes equally important and relevant, as measured by statistical performance indicators (SPI). This study aims to explore the association of financial inclusion (FI); environmental, social and governance (ESG); poverty; and SPI.

The panel data of 140 nations for nine years are gathered to explore the association of FI, ESG and poverty with the SPI. Panel data estimation is conducted to arrive at the results.

The findings of this study highlight mixed outcomes for FI. ESG is positively associated with SPI, but poverty is not associated with SPI. These findings imply that an increase in FI may reduce the statistical capacity of the nations. An increase in ESG increases the capacity. However, change in poverty does not influence the SPI. The recommendation based on this study’s outcome suggests auditing the FI and poverty vis-à-vis SPI to ensure SPI’s veracity and robustness in the long run.

The way in which the individual social, economic and environmental indicators influence the SPI needs to be tested to establish the veracity and robustness of the SPI, which is barely researched as observed in the literature.

The authors extend the World Bank's Logistics Performance Index (LPI) for 30 additional countries and 13 additional years. The authors develop an inexpensive method for extending survey data when frequent, universal surveys are unavailable. The authors identify groups of country characteristics that influence LPI scores.

Using data from the World Development Indicators—the broadest global dataset of country socioeconomic features—the authors test machine learning algorithms for their ability to predict the LPI. The authors examine importance scores to identify factors that influence LPI scores.

The best performing algorithm produces predictions on unseen data that account for nearly 90% of observed variation, and are accurate to within 6%. It performs twice as well as an OLS model with per capita income as the only predictor. Explanatory factors are business environment, economic structure, finance, environment, human development, and institutional quality.

Machine learning offers a simple, inexpensive way of extending the coverage of survey data. This dataset provides a richer picture of logistics performance around the world. The factors the authors identify as predicting higher LPI scores can help policymakers and practitioners target interventions.

This paper is one of the first applications of machine learning to extend coverage of an index based on an international survey. The authors use the new data to provide the most wide-ranging analysis of logistics performance across countries and over time. The output is an important resource for policymakers tracking performance, and researchers particularly in smaller and lower income countries. The authors also examine a wider range of explanatory factors for LPI scores than previous work.

Higher education (HE) in the UK has recently suffered financial pressure due to reduced central funding, and the requirement to widen student access. The estate is typically the second highest revenue expense and is an obvious target for efficiency gains. Sector‐wide statistics show there are opportunities for improving efficiency and many influential bodies have advocated space charging as a way of achieving them. This paper aims to investigate space performance indicators for evidence that space charging improves space use efficiency.

The approach used is a statistical analysis of space performance indicators for space charging and other higher education institution (HEIs).

Approximately one‐quarter of HEIs in the UK operated space charging in 2000‐2001 but only ten out of 31 space‐related performance indicators for the period 1998‐2001 suggest that increased efficiency results. Scrutiny of the background data shows they predominantly reflect differences in institutional wealth and activities, rather than space use management. Efficiency measures relating space to use provide no evidence of efficiency gains, suggesting that the application of charging as a space management tool is ineffective.

The methodology does not reveal the reasons for the disparity between theory and results of space charging. Qualitative research into the application of charging systems is required to provide an explanation.

The conclusions are important for HE managers who are considering implementing expensive systems to improve space efficiency. The results also shed light on the usefulness of space performance indicators for HE estates.

Although there have been many assertions that space charging will improve space use efficiency in the HE sector, this research provides evidence to the contrary.

Although the Social Progress Index offers a thorough overview of the top-ranked countries with a highly developed social performance, it assigns the same weight to all component scores, implying that each component has identical and independent contribution to the SPI. By removing these flawed assumptions, the purpose of this paper is to examine the causal relationships among component scores and identify the critical components for reform priorities.

The authors propose an alternative approach to exploring the causal relationships and prioritizing the underlying components of the SPI. The four-step methodology comprises cluster analysis, data mining, partial least square path modeling, and importance-performance matrix analysis.

The authors find evidence of causal interrelations between the 12 components of the SPI. To accelerate social progress, the authors suggest that policy makers should allocate resources in order of priority to personal freedom and choice, personal rights, access to advanced education, water and sanitation, access to information and communications, tolerance and inclusion, personal safety, shelter, ecosystem sustainability, nutrition and basic medical care, health and wellness, and, finally, access to basic knowledge.

Policy makers in government, business, and civil society should become aware of causal relationships among the 12 components of the SPI and select an appropriate methodology to prioritize areas where social improvement is most needed.

Allowing for unequal weighting and causal relationships between component scores of the SPI, the authors’ methodology is the first attempt to offer a concrete way to identify which areas of social progress should constitute priorities for policy reforms.

This paper aims to examine the performance of marginalized farmers in supply relationships with agri-tech firms in emerging rural agricultural economies. The complex relationship among the suppliers, dual relationship and knowledge transfer (KT) was studied. This paper empirically investigates the relationship between KT and supplier’s performance improvement (SPI) via buyer–supplier relationship (BSR).

Grounded on agency theory, a conceptual framework has been proposed to identify the mediation effect of BSR. The context deals with suppliers who are farmers in developing nations. The hypotheses were tested using confirmatory factor analysis and structural equation with a sample of 121 marginalized farmers from Indian states. The data was collected using a survey instrument designed by adapting the well-cited and validated measures. These marginalized farmers worked in collaboration with the agri-tech firms facilitating them with the KT.

The relationships established from the results also indicate the fact that KT is a powerful tool to make connections with farmers that lead to their performance improvement. The KT was found as a driver to improve performance (SPI) and the BSR acted as a positive mediator in this study. The complex relationships among the KT, BSR and SPI hold.

This paper can be subscribed to various nuanced understandings of the agricultural supply chain context in emerging economies, in the specialized cases where farmers belong to the marginalized communities. This study has the scope to replicate using a mixed-method approach in emerging economies beyond India. It also advances the agency theory literature in the supply chain discipline of emerging rural economies.

This study offers strategic implications for agri-tech practitioners, policymakers and academic debate. The marginalized farmers with KT and improved BSR can become a part of the mainstream value chain, their debts can be reduced, suicides can be prevented and the quality of their family life can be significantly improved.

This study makes a unique contribution by investigating how the agri-tech firms (non-traditional buyer) and supplier relationship and KT helps improve the economic sustainability of smallholder farmers in India. The authors immersed themselves in fieldwork by interacting and meeting in person with 121 farmers residing in the remotest of the remote rural areas across multiple states of India. This resulted in the collection of authentic data and capturing the ground realities from one of the fastest-growing and largest emerging economies.

Building energy efficiency retrofit (BEER) not only provides excellent opportunities to reduce overall energy consumption of buildings in a city but also encourages environmental protection, the rational use of resources, and occupants' healthcare, which all contribute towards the sustainability of existing buildings. However, there is a lack of effective performance indicators to measure the sustainability of BEER projects. The aim of this paper is to formulate a list of key performance indicators (KPI) for the sustainability assessment of BEER in hotel buildings.

First, a literature review and in‐depth interviews with industry experts and academic researchers were conducted, which filtered the performance indicators for assessing sustainability. Second, a questionnaire survey was conducted to collect data from various groups of experts to analyze the significance of the selected performance indicators. Finally, a model based on fuzzy set theory was designed to identify the key performance indicators (KPIs) for the sustainability of BEER.

Eight KPIs were identified based on fuzzy set theory in this study. They are: quality performance, hotel energy management, cost performance, project profitability, energy consumption and resources saving, health and safety, stakeholder satisfaction, and innovation and improvement.

The KPIs of sustainability of BEER identified for hotel buildings in China in this study can be useful reference for other similar research. However, with the different requirements for building types and building ownerships, the KPIs of sustainability of BEER for different buildings may be variable. The findings in this study may not be directly relevant to other types of building.

Key performance indicators for the sustainability assessment of BEER in hotel buildings in China are identified and analyzed in this study. The KPIs can help decision‐makers to identify an optimal solution between alternatives, which presents the maximum sustainability performance.

The purpose of this paper is to provide a broad overview of welfare schemes in India and their impact on social protection during a period of high economic growth. It summarizes India's performance with respect to select economic and social indicators relative to select low and middle-income countries in the Asia Pacific region. It further overviews trends in some key select economic and social indicators for India and discusses India's attainment in Social Protection relative to an index of such protection provided by the Asian Development Bank.

This paper uses a comparative statistical approach and evaluates India's performance in key social welfare areas vis-à-vis that of countries with economic performance comparable to that of India. It also evaluates India's progress along these parameters over time.

The basic messages of this paper are: first, compared to low and middle-income countries in the Asia Pacific India's economic performance has outstripped its performance in social and welfare indicators. Second, nevertheless India is spending less on social welfare programs and other welfare schemes than many countries in the Asia Pacific, including some of those whose economic performance has been less impressive than India's. Third, the efficiency and effectiveness of key welfare programs in India need to be substantially improved. Particular attention needs to be paid to female participation in and their access to social welfare programs.

Informed analyses of social sector spending in India and their impact on welfare outcomes are relatively scarce although descriptive studies of social sector spending and welfare schemes abound. This paper attempts to fill this gap with a cross-country as well as intertemporal analysis of India's performance in these key areas.

This study aims to evaluate the competitiveness of nations and seeks to answer the following research question: how does the competitiveness of nations include improvements in the quality of life, thus influencing and contributing to social progress in both social and economic indices?

This paper collected secondary data from the World Economic Forum and the socioeconomic dimensions of the Social Progress Imperative Index and considered the dimensions of these indices, which were demonstrated using Pearson’s correlation coefficient. The main focus was on the documentary analysis that was carried out to explain the realities of 121 countries from 2014 to 2017 as taken from these indices, considering the 10 countries at the top and bottom.

This study showed the use of new measures for the performance of nations that are less dependent on economics and focus more on social development, which may be a trend for the future of nations, and produce a more holistic view for the study. “Innovation” is the factor with the weakest relationship with social progress, which is justified by a weaker relationship with one of the subcategories, “basic human needs”, when analyzed in isolation. However, when the authors analyze the best and worst nations, the authors observe that economic factors are still prevalent, with the “institutions” and “infrastructure” factors being effective for improving competitiveness and the quality of life.

The findings represent a new, emerging configuration in country performance, but the study has its limitations, such as the use of only two pooled variables and the fact that it does not correlate their dimensions or variables.

This study can represents an expansion logic for measuring the performance of countries considering social factors. The main contributions of this study are its statistical evidence and documentary analysis of the relationship between economic and social variables. The main contribution of this paper is to show that over time (2014–2017) economic factors, as measured by the competitiveness index of nations, relate to aspects of social welfare, as measured by the social progress index.

The purpose of this paper is to identify the relationships among absorptive capacity (AC), organisational culture (OC), and software process improvement (SPI) implementation success based on capability maturity model integration (CMMI). Specifically, the aim of this study is to understand the roles of potential and realised AC in SPI success.

This study proposes a research model and examines the relations among firm AC, SPI success, and OC. The authors surveyed 56 Taiwanese firms that adopted the CMMI-based SPI programme and received official certification.

The findings indicate that potential and realised AC have significantly positive effects on SPI success. In particular, realized (AC) partially mediates the effects of potential AC on SPI success. Furthermore, the effects of potential and realised AC on SPI success are significantly moderated by the adhocracy and hierarchy OCs, respectively.

Given that the scope of this empirical study was limited to Taiwan, the findings might lack generalisability; however, this provides an opportunity for future research.

This is the first empirical study investigating the influence of AC on CMMI-based SPI success. The proposed research model also examines the moderating relationships of two types of OCs, namely adhocracy and hierarchy, on AC (potential and realized) and SPI success.

Sustainable production (SP) is a very broad area and the awareness and communication of the concept differ between varying levels in a company. The supposition is that the awareness and improvement of sustainability on shop floor level would improve, if a suitable set of indicators for measuring sustainability was available. The purpose of this paper is therefore to identify a list of performance indicators relevant for a production manager.

This paper presents a two-step analysis, where the first step is a literature review with the purpose of compiling a gross list of sustainability indicators relevant on shop floor level. In the second phase, the relevance of this list for production managers in Swedish small- and medium-sized enterprises (SMEs) is tested in a questionnaire survey.

The conclusion from the survey is that 27 out of 52 proposed indicators were relevant with statistical significance and that another 20 indicators were supported by at least 50 percent of the respondents. The respondents found the economic indicators to be most relevant for their purpose. However, the economic field seems to need more indicators in order to be more useful for daily operation.

This set of indicators may be beneficial for companies seeking relevant indicators to drive sustainability improvements.

This paper takes a new perspective on SP, as it focusses on shop floor production, which is possible to influence for a production manager.