Search results

This paper aims to identify and empirically analyze useful and applicable metrics for measuring and managing the sustainability performance of small and medium-sized enterprises (SMEs).

To achieve the objective of the paper, potential metrics were adopted from previous research related to industrial sustainability and an empirical analysis was carried to assess the applicability of the metrics by collecting empirical data from Italian footwear SMEs using a structured questionnaire. The SMEs were selected using a convenience sampling method.

The results of the within-case analysis and the cross-case analysis indicate that the majority of the metrics were found to be useful and applicable to each of the SMEs and across the SMEs, respectively. These metrics emphasized measuring industrial sustainability performance related to financial benefits, costs and market competitiveness for the economic sustainability dimension; resources for the environmental sustainability dimension; and customers, employees and the community for the social sustainability dimension.

Apart from the within-case analysis and cross-case analysis, it was not possible to conduct statistical analysis since a small number of SMEs were accessible to collect empirical data.

The findings of the paper have considerable academic, managerial and policy implications and will provide a theoretical basis for future research on measuring and managing industrial sustainability performance. By providing a set of empirically supported metrics based on the triple bottom line approach (i.e. economic, environmental and social metrics), this paper contributes to the existing knowledge in the field of industrial sustainability performance measurement.

In confronting the challenge of climate change and progressing towards dual carbon goals, China is actively implementing low-carbon city pilot policy. This paper aims to focus on the potential impact of this policy on enterprise green governance, aiming to promote the reduction and balance of carbon emissions.

Based on the panel data of China's large-scale industrial enterprises from 2007 to 2013, this paper uses the Difference-in-differences (DID) method to study the impact and path mechanism of the implementation of low-carbon city pilot policy on enterprise green governance. Heterogeneity analysis is used to compare the effects of low-carbon city pilot policy in different regions, different enterprises and different industries.

The low-carbon pilot can indeed effectively enhance corporate green governance, a conclusion that still holds after a series of robustness tests. The low-carbon city pilot policy mainly enhances enterprise green governance through two paths: an industrial structure upgrade and enterprise energy consumption, and it improves green governance by reducing enterprise energy consumption through industrial structure upgrade. The impact of low-carbon city pilot policy on enterprise green governance shows significant differences across different regions, different enterprises and different industries.

This paper examines the impact of low-carbon city pilot policy on enterprise green governance. However, due to availability of data, there are still some limitations to be further tackled. The parallel trend test in this paper shows that the pilot policy has a significant positive effect on the green governance of enterprises. However, due to serious lack of data in some years, the authors only selected the enterprise data of a shorter period as our experimental data, which leads the results to still have certain deficiencies. For the verification of the impact mechanism, the conclusions obtained in this paper are relatively limited. Although all the mechanism tests are passed, the reliability of the results still needs to be further tested through future data samples. In addition, as the pilot policy of low-carbon cities is still in progress, the policy can be tracked and analysed in the future as more data are disclosed, and further research can be carried out through dimensional expansion.

Low-carbon city pilot policy plays an important role in inducing the green governance of enterprises. Therefore, policy makers can continue to strengthen the construction of low-carbon city pilots by refining pilot experience, building typical cases, actively promoting pilot policy experience, expanding pilot scope and enhancing the implementation efficiency of pilot policy nationwide, which will contribute to the optimization and upgrading of the regional industrial structure at the urban level and will provide experience and reference for the synergistic implementation plan of pollution reduction and carbon reduction.

The impact of the low-carbon city pilot policy on enterprise green governance not only exists in two separate paths of urban industrial upgrading and enterprise energy consumption but also exists in a chain transmission path from macro to micro. The authors find that the effect value of each influence path is different, and there is an obvious leading influence path for the role of enterprise green governance. Therefore, in the process of implementing a low-carbon city pilot policy, policies should be designed specifically for different mechanisms. Moreover, complementing and coordinating several paths should be advocated to give full play to the green governance effect of enterprises brought by different paths and to further expand the scope of industries and enterprises where policies play a role.

To the best of the authors’ knowledge, for the first time, this paper connects macro mechanisms with micro mechanisms, discovering a macro-to-micro transmission mechanism in the process of low-carbon city pilot policy affecting enterprise green governance. That is, the low-carbon city pilot policy can facilitate industrial structure upgrading, resulting in reduced enterprise energy consumption, ultimately enhancing enterprise green governance.

Industry 4.0 is a promising concept that allows industries to meet customers’ demands with flexible and resilient processes, and highly personalised products. This concept is made up of different dimensions. For a long time, innovative digital technology has been thought of as the only dimension to succeed in digital transformation projects. Other dimensions have been identified such as organisation, strategy, and human resources as key while rolling out digital technology in factories. From these findings, researchers have designed industry 4.0 theoretical models and then built readiness models that allow for analysing the gap between the company initial situation and the theoretical model. Nevertheless, this purely deductive approach does not take into consideration a company’s background and context, and eventually favours one single digital transformation model. This article aims at analysing four actual digital transformation projects and demonstrating that the digital transformation’s success or failure depends on the combination of two variables related to a company’s background and context. This research is based on a double approach: deductive and inductive. First, a literature review has been carried out to define industry 4.0 concept and its main dimensions and digital transformation success factors, as well as barriers, have been investigated. Second, a qualitative survey has been designed to study in-depth four actual industry digital transformation projects, their genesis as well as their execution, to analyse the key variables in succeeding or failing. 46 semi-structured interviews were carried out with projects’ members; interviews have been analysed with thematic content analysis. Then, each digital transformation project has been modelled regarding the key variables and analysed with regards to succeeding or failing. Investigated projects have consolidated the models of digital transformation. Finally, nine digital transformation types have been identified.

The objective of this study is to examine current business and management research on “Industry 4.0 base technologies” and “business models” to shed light on this vast literature and to point out future research agenda.

The authors conducted a bibliometric analysis of scientific publications based on 482 documents collected from the Scopus database and a co-citation analysis to provide an overview of business model studies related to Industry 4.0 base technologies. After that a qualitative analysis of the articles was also conducted to identify research trends and trajectories.

The results reveal the existence of five research themes: smart products (cluster 1); business model innovation (cluster 2); technological platforms (cluster 3); value creation and appropriation (cluster 4); and digital business models (cluster 5). A qualitative analysis of the articles was also conducted to identify research trends and trajectories.

First, the dataset was collected through Scopus. The authors are aware that other databases, such as Web of Science, can be used to deepen the focus of quantitative bibliometric analysis. Second, the authors based this analysis on the Industry 4.0 base technologies identified by Frank et al. (2019). The authors recognize that Industry 4.0 comprises other technologies beyond IoT, cloud computing, big data and analytics.

Drawing on these analyses, the authors submit a useful baseline for developing Industry 4.0 base technologies and considering their implications for business models.

In this paper, the authors focus their attention on the relationship between technologies underlying the fourth industrial revolution, identified by Frank et al. (2019), and the business model, with a particular focus on the developments that have occurred over the last decade and the authors performed a bibliometric analysis to consider all the burgeoning literature on the topic.

This study analyzed Korea's relations table through network analysis. In particular, among the centralities, eigenvector centrality, PageRank centrality and degree were used. The author studied which network characteristics affected the value-added rate.

A network analysis method was used.

It is the inward relationship that affects the value-added ratio of Korea's industries and the outward relationship has less influence. In particular, the inward relationship not only acts as a cost but also has an effect on the rate of added value recently.

Since the three years of 2010, 2015 and 2019 are the target, the data are somewhat insufficient to generalize.

As for the value-added ratio of an industry, input is more important than output (sales). Therefore, where the input is received is very important.

It is possible to increase the understanding of the determinants of the value-added rate of Korean industries.

(1) It was clarified which side is inward or outward in determining the industry in Korea. (2) The relationship between PageRank, eigenvector centrality and degree was analyzed in Korean cases. (3) Input is a cost and acts to increase added value.

This study aims to analyze and compare the relationship between international trade in global value chains (GVC) and greenhouse gas (GHG) emissions for Brazil and China from 2000 to 2016.

The input-output method apply to multiregional tables from Eora-26 to decompose the GHG emissions of the Brazilian and Chinese productive structure.

The data reveals that Chinese production and consumption emissions are associated with power generation and energy-intensive industries, a significant concern among national and international policymakers. For Brazil, the largest territorial emissions captured by the metrics come from services and traditional industry, which reveals room for improving energy efficiency. The analysis sought to emphasize how the productive structure and dynamics of international trade have repercussions on the environmental dimension, to promote arguments that guide the execution of a more sustainable, productive and commercial development strategy and offer inputs to advance discussions on the attribution of climate responsibility.

The metrics did not capture emissions related to land use and deforestation, which are representative of Brazilian emissions.

Comparative analysis of emissions embodied in traditional sectoral trade flows and GVC, on backward and forward sides, for developing countries with the main economic regions of the world.

This study aims to theoretically and experimentally investigate the literature on university–industry linkages (UILs) through a systematic literature review and bibliometric analysis. Seven research questions were addressed in the present study: (1) descriptive characteristics of the literature on UIL, (2) trends of annual scientific publications on UIL, (3) the most relevant and high-impact sources on UIL, (4) the most globally cited articles on UIL, (5) the most relevant countries on UIL, (6) outcomes of Bradford's Law of Scattering and Lotka's Law of scientific productivity and (7) the trending research areas and avenues for future studies on UIL.

Systematic literature review and bibliometric analysis mapping techniques were applied to the present study to analyze 907 articles extracted from the Scopus database. Analysis tools used were Biblioshiny software and VOSviewer software.

Findings show that the UIL is a progressively growing discipline with a record of a 5.71% average annual growth rate in scientific production each year from 1970 to 2023. The United States, China and the United Kingdom were the most productive countries in the field of UIL in terms of total scientific production and citations. Academic entrepreneurship, industrial ecology, social network analysis, active learning, engineering education, health economics, public health, university–industry relationships, communication, causal layered analysis and competitiveness are the potential avenues for future researchers in the field of UIL based on the thematic map of keywords analysis.

This study contributes to the debate on UIL by offering a comprehensive literature review. The findings of the current study will benefit graduates, universities, industries and the community at large.

The purpose of this paper is to offer a comprehensive overview of current research on customer behavior in the business-to-business (B2B) context and propose a research agenda for future studies. Despite being a relatively recent area of interest for academics and practitioners, a literature review that synthesizes existing knowledge into coherent topics and outlines a research agenda for future research is still lacking.

Drawing on a systematic literature review of 219 papers and using a text-mining approach based on the Latent Dirichlet Allocation algorithm, this paper enhances the existing knowledge of B2B customer behavior and provides a descriptive analysis of the literature.

From this review, ten major research topics are found and analyzed. These topics were analyzed through the lens of the Theory, Context, Characteristics and Method framework, providing a summary of key findings from prior studies. Additionally, an integrative framework was developed, offering insights into future research directions.

This study presents a novel contribution to the field of B2B by providing a systematic review of the topic of customer behavior, filling a gap in the literature and offering a valuable resource for scholars and managers seeking to advance the field.

This study conducts a comparative analysis of the impact of educational mismatch on Spanish wages. This paper aims to focus on the industrial, construction and service sectors at three levels of disaggregation: sector, occupation and gender.

The over-education, required education and under-education (ORU model), was applied to data from the 2018 Spanish Wages Structure Survey conducted by the Spanish National Statistics Institute.

The industrial sector is the one that best manages over-education by offering the highest returns to each year of over-education. It is also the sector that most values the education of women, particularly those in highly qualified positions.

This study compares the wage effects of educational mismatch in the service, industry and construction sectors. Previous literature has ignored the latter sectors in this field of study, but the results of the present study show that the industrial sectors significantly value and remunerates worker education. Therefore, it may be worthy to focus certain economic and social policies on this sector, to contribute to reducing gender wage gaps and gender employment discrimination in the economy.

The purpose of this paper is to identify the constituent parts of learning in the manufacturing work context and understand why these parts are key in the learning of the employees.

The data was collected from two sources: a literature review of the Information Systems literature to establish an initial picture of what learning in relation to digital technologies entails and in-depth interviews with engineers in the automotive industry whose knowledge-intensive work is exposed to substantial digital transformation.

The authors first identified three constituent parts for learning: change, reflection and deliberation. When the authors cross-checked the initial findings through in-depth interviews with the engineers, it was found that these three themes trigger learning through three different mechanisms, that is, balancing newness, finding point of reference and organizing actively. Thus, the findings of this paper extend beyond a categorical identification of what constitutes learning to also illustrate why learning entails these constituent parts.

This paper implies that progressive learning requires active organizing of learning stages. The data is limited to the review of the Information Systems field. The authors have also only focused on the automotive industry as the representative sector in the manufacturing industry.

Applying the model of progressive learning can be a primary way to actively plan and organize learning opportunities for employees. This is key for supporting learning culture in organizations that are exposed to continuous and disruptive changes.

A significant part of social sustainability is based on sustainable employability and feelings of contentment at work. This paper is an attempt to highlight how sustainable employability can be achieved by providing effective learning opportunities at work.

The originality of this paper emerges from two sources. First, the authors conducted the literature review and in-depth interviews by devising innovative methods because of the challenges of identifying when (informal) learning has occurred at work. Second, the authors owe the in-depth interviews to the first author’s extensive familiarity with the automotive industry and the knowledge and rapport acquired through her prior longitudinal research on the engineers’ work. It was this background that allowed the authors to find out when these engineers were about to leave the firm because of discontent about their competence development.