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This study empirically examines the impact of climate change and agricultural research and development (R&D) as well as their interaction on agricultural productivity in 12 selected Asian and Pacific countries over the period of 1990–2018.

Various estimation methods for panel data, including Fixed Effects (FE), the Feasible Generalized Least Squares (FGLS) and two-step System Generalized Method of Moments (SGMM) were used.

Results show that both proxies of climate change – temperature and precipitation – have negative impacts on agricultural productivity. Notably, agricultural R&D investments not only increase agricultural productivity but also mitigate the detrimental impact of climate change proxied by temperature on agricultural productivity. Interestingly, climate change proxied by precipitation initially reduces agricultural productivity until a threshold of agricultural R&D beyond which precipitation increases agricultural productivity.

The findings imply useful policies to boost agricultural productivity by using R&D in the context of rising climate change in the vulnerable continent.

This study contributes to the literature in two ways. First, this study examines how climate change affects agricultural productivity in Asian and Pacific countries – those are most vulnerable to climate change. Second, this study assesses the role of R&D in improving agricultural productivity as well as its moderating effect in reducing the harmful impact of climate change on agricultural productivity.

Emerging economies have been highlighted as an important growth source of the global economy. However, this group of countries has not received enough academic attention yet. Therefore, this study aims to identify the impact of research and development (R&D) expenditure on economic growth in emerging economies.

The theoretical framework of the production function is applied to quantitatively analyse the impact of R&D expenditure on economic growth with a sample of 29 emerging economies in the period between 1996 and 2019.

The panel cointegration test confirms the existence of long-run cointegration relationships between economic growth and independent variables in these emerging economies. Besides, the estimated results show that the national R&D expenditure has positive effects on economic growth from both direct and interaction dimensions. This evidence has filled the empirical research gap in the R&D-growth nexus in the case of emerging economies. Finally, while gross capital and education have positive impacts on growth, corruption has a harmful effect on economic growth in these countries.

The results highlight that policymakers should enhance R&D expenditure and R&D activities as the key national development strategy. The investment in R&D not only helps emerging economies avoid the middle-income trap but also pushes these countries to successfully join the group of developed countries.

To the best of the authors’ knowledge, this research is among the first to examine the impact of R&D expenditure on economic growth with a homogeneous sample of emerging economies. The results are obviously helpful for policymakers to use R&D as the key development strategy for supporting economic growth in emerging economies in the future.

This study empirically investigates the impacts of technological innovation and operational efficiency on environmental performance and the moderating effects of environmental orientation.

We develop a conceptual framework based on the Porter Hypothesis. We collect a sample of 850 listed firms in China between 2010 and 2019. The fixed effect model was used to analyse the data.

The empirical findings reveal that technological innovation indirectly enhances environmental performance through operational efficiency and partially mediates this impact. We also find that environmental orientation strengthens the positive impacts of technological innovation and operational efficiency on environmental performance.

This study contributes to the literature by revealing that technological innovation is positively associated with operational efficiency and environmental performance, which suggests that technological innovation can simultaneously enhance business and environmental performance. Hence, this study provides empirical support for the Porter Hypothesis. The results also extend the Porter Hypothesis by revealing how technological innovation affects environmental performance and under what conditions technological innovation has a greater impact on environmental performance.

This paper aims to analyze the thematic content of research addressing the relation between board of directors (BoD) and business transformation (BT) to obtain better understanding of status and to derive future areas of study.

This paper reviews literature through a bibliometric analysis based on co-occurrence of articles published in Web of Science Core Collection ™ (WoS) between 1990 and 2022, identifying key concepts, setting network of relations and identifying the strategic importance of clusters of concepts. Findings and implications are discussed, future lines of research are presented and limitations are noted.

Thematic research on boards addressing transformation shifted from the analysis of individuals' traits to an organizational approach with majority of research centered on the role of boards under different theories and the consequences of strategic changes on firm's performance. Further research is around gender diversity, sustainability and the moderating role of ownership structure and business culture.

Some limitations are also noted. This analysis considered articles indexed by WoS for Q1+Q2 publications as source of literature, while including others such as Scopus would increase knowledge base. Also, to identify main streams of research, the authors considered keywords with cumulative occurrence spanning from 30% to 40% while increasing this percentage would add terms that might improve precision to the connections among keywords. Other techniques could have been used such as co-citation or bibliographic coupling, although the authors find these as better suited to investigate the basic structure behind the foundational knowledge of the topic while the authors’ intention was to understand the positioning of study fields regarding the degree of research progress.

This paper presents some practical implications for future researchers. Those who wish to leverage previous evidence to address new research questions might look into principal themes covering BoD dynamics and composition to exert CG, and the relation between strategic decisions and performance measured by different variables. Those who wish to position their research as new findings to shed light on dilemmas, might find opportunities in the fields of climate change-sustainability, R&D for growth and innovation under the perspective of intangible assets.

This paper, is the first to the best of the authors’ knowledge, to identify research clusters for the intersection of boards and transformation and to determine their stage of development.

本文旨在分析探討董事會與業務轉型之間的關係的學術研究的專題內容，以能對有關課題的研究狀況有更深入的了解，並擬從分析中取得未來可供研究的範疇。

本文透過科學計量分析法來進行文獻探討。方法乃基於在1990年至2022年期間在Web of Science Core Collection 刊載的學術論文的共現分析而進行; 透過這個研究方法，研究人員建立了聯繫的網絡，並確認了各個概念群組的策略重要性。在本文中，研究結果和研究結果帶來的啟示會被討論，未來的研究領域和方針也會得到說明，研究的局限也會被認定和記錄下來。

探討董事會而又涉及業務轉型的專題研究，由當初集中探討董事個人的特質、轉移到現在研究整體的組織理念和處事取向，而就後者來說，大部份的研究都集中於在不同的理論框架裡董事會所扮演的角色，以及因策略上的改變而為公司的業績帶來的影響。進一步的學術研究都是圍繞著性別多元化、可持續性、所有權結構所扮演的緩和角色和商業文化的研究。

盡我們所知，本文乃為首篇學術論文，去鑑定關於董事會與業務轉型之間的關聯的研究集群，也是首篇學術論文，去確定這些研究集群的發展階段。

The purpose of this paper is to understand if and how industrialized house building (IHB) could support productivity developments for housebuilding on project and industry levels. The take is that fragmentation of construction is one explanation for the lack of productivity growth, and that IHB could be an integrating method of overcoming horizontal and vertical fragmentation.

Singe-factor productivity measures are calculated based on data reported by IHB companies and compared to official produced and published research data. The survey covers the years 2013–2020 for IHB companies building multi-storey houses in timber. Generalization is sought through descriptive statistics by contrasting the data samples to the used means to control vertical and horizontal fragmentation formulated as three theoretical propositions.

According to the results, IHB in timber is on average more productive than conventional housebuilding at the company level, project level, in absolute and in growth terms over the eight-year period. On the company level, the labour productivity was on average 10% higher for IHB compared to general construction and positioned between general construction and general manufacturing. On the project level, IHB displayed an average cost productivity growth of 19% for an employed prefabrication degree of about 45%.

Empirical evidence is presented quantifying so far perceived advantages of IHB. By providing analysis of actual cost and project data derived from IHB companies, the article quantifies previous research that IHB is not only about prefabrication. The observed positive productivity growth in relation to the employed prefabrication degree indicates that off-site production is not a sufficient mean for reaching high productivity and productivity growth. Instead, the capabilities to integrate the operative logic of conventional housebuilding together with logic of IHB platform development and use is a probable explanation of the observed positive productivity growth.

Performance framework (PF) is a well-established practice to measure innovation performance and identify improvement opportunities. However, whether PFs academic research are applicable to companies remains unclear, as well as their support in the definition of improvement actions. This study aims to present the implementation and assessment of a new and updated PF proposed in previous research in a real industrial context.

The PF was implemented through an in-depth case study carried out in a European machinery manufacturer and further assessed by practitioners.

The results indicate that the PF enabled the creation of a multidimensional view of the innovation performance and the definition of improvement projects in the company. Additionally, the findings also reveal an overall positive assessment of the PF by senior managers who work with the innovation process.

As a case study, this research is inherently limited in the extent to which results can be generalised. Thus, the analyses are reductive and rationalising. Future research is needed to assess the replicability of the PF.

The study's practical contribution is based on the combination of insights and steps that provide a straightforward and actionable approach for the company to improve performance.

This study aims to advance the importance of implementing the new and updated PF after its proposition, which is often overlooked in preceding research. Furthermore, the assessment of the PF also enables to infer its value to the company's employees.

The concept of productivity is central to performance management and decision-making, although it is complex and multifaceted. This paper aims to describe a methodology based on the use of Big Data in a cluster analysis combined with a data envelopment analysis (DEA) that provides accurate and reliable productivity measures in a large network of retailers.

The methodology is described using a case study of a leading kitchen furniture producer. More specifically, Big Data is used in a two-step analysis prior to the DEA to automatically cluster a large number of retailers into groups that are homogeneous in terms of structural and environmental factors and assess a within-the-group level of productivity of the retailers.

The proposed methodology helps reduce the heterogeneity among the units analysed, which is a major concern in DEA applications. The data-driven factorial and clustering technique allows for maximum within-group homogeneity and between-group heterogeneity by reducing subjective bias and dimensionality, which is embedded with the use of Big Data.

The use of Big Data in clustering applied to productivity analysis can provide managers with data-driven information about the structural and socio-economic characteristics of retailers' catchment areas, which is important in establishing potential productivity performance and optimizing resource allocation. The improved productivity indexes enable the setting of targets that are coherent with retailers' potential, which increases motivation and commitment.

This article proposes an innovative technique to enhance the accuracy of productivity measures through the use of Big Data clustering and DEA. To the best of the authors’ knowledge, no attempts have been made to benefit from the use of Big Data in the literature on retail store productivity.

This paper aims to define the efficiency achieved by urban transport companies in Spain concerning the resources they use, considering the type of management used for implementation, public-private, and size.

This study consisted of an analysis of the efficiency of 229 public-private urban transport operators during the period 2012–2021 using Data Envelopment Analysis, the Malmquist Index and inference estimators to determine productivity, efficiency change into Pure Technical Efficiency Change (PTECH), and scale efficiency change.

Based on the efficiency analysis, the authors concluded that of the 229 companies studied, more than 35 were inefficient in all analysed periods. Considering the sample used, direct management is considered significantly more efficient. It cannot be concluded that the size of these companies influences their efficiency, as the data show unequal development behaviours in the studied years.

This study provides arguments on whether there is a significant difference between the two types of management in the urban transport sector. It also includes firm size as a study variable, which has not been previously considered in other studies related to urban transport efficiency. Efficiency should be a crucial factor in determining funding allocation in this sector, as it encourages operators to optimize and improve their services.

This paper aims to overcome the inability of both comparing loss costs and accounting for production resource losses of Overall Equipment Effectiveness (OEE)-related approaches.

The authors conducted a literature review about the studies focusing on approaches combining OEE with monetary units and/or resource issues. The authors developed an approach based on Overall Equipment Cost Loss (OECL), introducing a component for the production resource consumption of a machine. A real case study about a smart multicenter three-spindle machine is used to test the applicability of the approach.

The paper proposes Resource Overall Equipment Cost Loss (ROECL), i.e. a new KPI expressed in monetary units that represents the total cost of losses (including production resource ones) caused by inefficiencies and deviations of the machine or equipment from its optimal operating status occurring over a specific time period. ROECL enables to quantify the variation of the product cost occurring when a machine or equipment changes its health status and to determine the actual product cost for a given production order. In the analysed case study, the most critical production orders showed an actual production cost about 60% higher than the minimal cost possible under the most efficient operating conditions.

The proposed approach may support both production and cost accounting managers during the identification of areas requiring attention and representing opportunities for improvement in terms of availability, performance, quality, and resource losses.

This study investigates the optimum size for manufacturing firms and the impact of subcontracting on firms' likelihood of achieving their optimal scale in Vietnam.

Using data from the enterprise census in 2017 and 2021, the paper first estimates the production function to identify the optimum firm size for manufacturing firms and then, applies the logit model to investigate factors associated with the optimal firm size.

The study reveals that medium-sized firms exhibit the highest level of productivity. Nevertheless, a consistent trend emerges, indicating that nearly 90% of manufacturing firms in Vietnam operated below their optimal scale in both 2017 and 2021. An analysis of the impact of subcontracting on firms' likelihood to achieve their optimal scale emphasizes its crucial role, especially for foreign firms, exerting an influence nearly five times greater than that of the judiciary system.

The paper's findings offer crucial policy implications, suggesting that initiatives aimed at enhancing the overall productivity of the manufacturing sector should prioritise facilitating contract arrangements to encourage firms to reach their optimal size. These insights are also valuable for other countries with comparable firm size distributions.

This paper provides the first empirical evidence on the relationship between firm size and productivity as well as the role of subcontracting in firms' ability to reach their optimal scale in a country with a right-skewed distribution of firm sizes.