Search results

This study aims to develop a polymer cement-based waterproof coating with self-healing capability to efficiently and intelligently solve the building leakage caused by cracking of waterproof materials, along with excellent durability to prolong its service life.

Ion chelators are introduced into the composite system based on ethylene vinyl acetate copolymer emulsion and ordinary Portland cement to prepare self-healing polymer cement-based waterproof coating. Hydration, microstructure, wettability, mechanical properties, durability, self-healing performance and self-healing products of polymer cement-based waterproof coating with ion chelator are investigated systematically. Meanwhile, the chemical composition of self-healing products in the crack was examined.

The results showed that ion chelators could motivate the hydration of C₂S and C₃S, as well as the formation of hydration products (C-S-H gel) of the waterproof coating to improve its compactness. Compared with the control group, the waterproof coating with ion chelator had more excellent water resistance, alkali resistance, thermal and UV aging resistance. When the dosage of ion chelator was 2%, after 28 days of curing, cracks with a width of 0.29 mm in waterproof coating could fully heal and cracks with a width of 0.50 mm could achieve a self-healing efficiency of 72%. Furthermore, the results reveal that the self-healing product in the crack was calcite crystalline CaCO₃.

A novel ion chelator was introduced into the composite coating system to endow it with excellent self-healing ability to prolong its service life. It has huge application potential in the field of building waterproofing.

Based on the extended resource-based view (ERBV), this paper aims to investigate the relationship between sustainable supply chain management (SSCM), dynamic capabilities (DCs) and enterprise economic performance (EEP). Both the direct effects of SSCM on economic performance and the mediation effect of DCs are investigated. This empirical study also examines the moderating role of firm size.

This study applies hierarchical regression analyses to test our hypotheses, and then the mediation test was performed using the macro PROCESS. Data were collected from 178 Chinese manufacturing firms.

The findings show that SSCM practices significantly and positively influence both economic performance and DCs. The results indicate that DCs partially mediate the relationship between SSCM practices and EEP. Moreover, firm size has a moderating effect on external SSCM practices that influence EEP, but the moderating effect was not found to be significant for the effects of internal SSCM practices on economic performance and SSCM practices on DCs.

This study reveals insights into the potential benefits for large enterprises and SMEs related to the utilization of SSCM practices in China and puts forward differentiated suggestions for SSCM practices in large enterprises and SMEs.

Drawing on the ERBV, this study provides a deeper perspective on the relationship between SSCM and EEP by regarding DCs as a mediating variable and firm size as a moderating variable.

Green sustainability has become a critical challenge for businesses to execute green supply chain management (GSCM). Most of the literature on GSCM emphasizes regulations as drivers and few pieces of research are conducted from an internal organizational culture view. This study aims to use the cultural perspective of market orientation (MO) and draws on both the natural resource-based view (NRBV) and dynamic capability view (DCV) to explore the relationships among green market orientation (GMO), GSCM capability and organizational performance.

A total of 1,000 survey questionnaires were distributed to the Taiwanese electronics industry and 207 valid questionnaires were collected. Data was analyzed using structural equation modeling.

The results show that GMOs have a significant positive impact on GSCM capability, environmental performance and economic performance. Moreover, GSCM capability is positively related to environmental and economic performance. The results also show that GMOs have a significant indirect influence on environmental performance and economic performance through GSCM capability.

The findings of this study suggest how Taiwan’s electrical and electronic manufacturers, while faced with pressure from competitors, customers and regulations (i.e. waste electrical and electronic equipment directive, Restriction of Hazardous Substances Directive and energy-using products directives), should efficiently and effectively implement GMO and enhance GSCM capability to improve organizational performance.

This study fills up the gap between MO and performance indistinct relationships. It has also integrated two perspectives, namely, NRBV and DCV, to explain GSCM capability as a mediator between GMO and organizational performance relationship and to examine the relationships among GMO, GSCM capability and organizational performance.

With rapid industrialization and urbanization, municipal solid waste (MSW) management has become a serious challenge worldwide, especially in developing countries. The Beijing Municipality is a representative example of many local governments in China that are facing MSW management issues. Although there have been studies in the area of MSW management in the literature, less attention has been devoted to developing a structured framework that identifies and interprets the barriers to MSW management in megacities, especially in Beijing. Therefore, this study focuses on identifying a comprehensive list of barriers affecting the successful implementation of MSW management in Beijing.

Through an extensive review of related literature, 12 barriers are identified and classified into five categories: government, waste, knowledge dissemination, MSW management process and market. Using an integrated approach including the decision-making trial and evaluation laboratory (DEMATEL), maximum mean de-entropy algorithm (MMDE) and interpretive structural modeling (ISM), a conceptual structural model of MSW implementation barriers is constructed to provide insights for industrial decision-makers and policymakers.

The results show that a lack of economic support from the government, imperfect MSW-related laws and regulations, the low education of residents and the lack of publicity of waste recycling knowledge are the main barriers to MSW management in Beijing. Combined with expert opinions, the paper provides suggestions and guidance to municipal authorities and industry practitioners to guide the successful implementation of MSW management.

The findings of this study can provide a reference for MSW management in other metropolises in China and other developing countries.

This study proposes a hybrid DEMATEL-MMDE-ISM approach to resolve the subjectivity issues of the traditional ISM approach and it analyzes the barriers that hinder MSW management practices in Beijing.

Nowadays, a prominent research area is the development of competitive advantages in companies, due to their environmental commitment and orientation. Based on resource-based view (RBV) and institutional theory (InT), this paper aims to investigate the influence of internal and external orientation on businesses' sustainable performance while considering the effect of sustainable supply chain management (SSCM) practices.

Data from 351 manufacturing companies in the Kingdom of Saudi Arabia have been collected and analysed through structural equation modelling (SEM) using the partial least squares (PLS) method.

The results indicated that both internal and external environmental orientation have important effects on SSCM practices, which in turn have a considerable beneficial effect on environmental, social and economic performance.

Although SSCM is constantly gaining ground in the literature, most SSCM research and models examine its effects, antecedents or motivation, mainly adopting a qualitative approach. Research on the topic adopting a large-scale empirical approach is still limited. In this context, this study contributes to the SSCM management literature by exploring the role of environmental orientation in facilitating the adoption of SSCM practices and improving companies' performance.

Agricultural carbon productivity considers the dual goals of “agricultural economic growth” and “carbon emission reduction”. Improving agricultural carbon productivity is a requirement for promoting green and low-carbon development of agriculture. Agricultural production agglomeration is widespread worldwide, but the relationship between agricultural production agglomeration and agricultural carbon productivity is inconclusive. This paper aims to study the impact of agricultural production agglomeration on agricultural carbon productivity, which is conducive to a better understanding of the relationships among agglomeration, agricultural economic development and carbon emission, better planning of agricultural layout to build a modern agricultural industrial system and achieve the goal of carbon peaking and carbon neutrality.

Based on China's provincial data from 1991 to 2019, this paper uses non-radial directional distance function (NDDF) and Metafrontier Malmquist–Luenberger (MML) productivity index to measure total factor agricultural carbon productivity. Subsequently, using a panel two-way fixed effect model to study the effect and mechanism of agricultural production agglomeration on agricultural carbon productivity, and the two-stage least squares method (IV-2SLS) is used to solve endogeneity. Finally, this paper formulates a moderating effect model from the perspective of the efficiency of agricultural material capital inputs.

The empirical results identify that Chinese provincial agricultural carbon productivity has an overall growth trend and agricultural technological progress is the major source of growth. There is an inverted U-shaped relationship between agricultural production agglomeration and agricultural carbon productivity. The input efficiency of agricultural film, machine and water resources have moderating effects on the inverted U-shaped relationship. Agricultural production agglomeration also promotes agricultural carbon productivity by inhibiting agricultural carbon emissions in addition to affecting agricultural input factors and its internal mechanisms are agricultural green technology progress and rural human capital improvement.

This paper innovatively adopts the NDDF–MML method to measure the total factor agricultural carbon productivity more scientifically and accurately and solves the problems of ignoring group heterogeneity and the shortcomings of traditional productivity measurement in previous studies. This paper also explains the inverted U-shaped relationship between agricultural production agglomeration and agricultural carbon productivity theoretically and empirically. Furthermore, from the perspective of agricultural material capital input efficiency, this paper discusses the moderating effect of input efficiency of fertilizers, pesticides, agricultural film, agricultural machines and water resources on agricultural production agglomeration affecting agricultural carbon productivity and answers the mechanism of carbon emission reduction of agricultural production agglomeration.

The purpose of this study is to categorize and analyse the drivers and barriers of Lean Manufacturing (LM) and subsequently, based on the structural model develop a house of lean management which will give an idea to the academicians and practitioners about the factors that are critical to implement lean practices in an organization.

A list of drivers and barriers was prepared based on the literature review and opinions from experts. Total Interpretive Structural Modelling (TISM) was utilized to build a structural hierarchy of the drivers and barriers of LM. The structural hierarchy was utilized to build the house of lean management.

Based on the hierarchy developed, the elements (drivers and barriers) of LM are classified into three groups: bottom-level, middle-level and top-level elements. To develop a house of lean management, bottom-level of elements were considered as a foundation, middle-level elements were considered as pillars and top-level elements were considered as a beam. Finally, foundation, pillars and beam of the house were used to support the roof (which is value to customers and profitability to firm).

The outcome of this research can assist researchers as well as practitioners to enhance the significant drivers and to reduce the impact of hazardous barriers for the better implementation of lean practices.

This research is a novel approach, as it visibly demonstrates both the drivers and barriers, examines the interrelationships among them in order and shows them pictorially as the house of lean management.

This study aims to examine the international joint venture (IJV) partnership strategy in Europe from an institutional perspective. A firm operating in a foreign country via an IJV can partner with a local firm from the host country, a firm from the same home country or a firm from a third country. This study takes the first step in examining the determinants of these partner choices.

This study tests hypotheses based on a data set of 637 IJVs in Europe.

Foreign firms are less likely to operate in a partnership with a firm from the home country or from a third country (compared to operate in a partnership with a local firm) when the host country institutions are weaker or institutional distance is larger. Also, foreign firms’ disinclination to operate in a partnership with a firm from the home/third country when the host country institutions are weaker or institutional distance is larger will diminish with greater host-country experience.

This study provides important insights for firms for evaluating partner choice and potential collaborations in the European region with heterogenous institutions.

The partner choice among the above three forms has been neglected in the literature. This study first conceptualized that the institutional profile of the host country and institutional distance between the host country and the home country can determine the partner choice.

The purpose of this paper is to identify and screen continuous innovation capability enablers (CICEs) in Indonesia’s manufacturing sectors, develop a relationship among these enablers and determine their driving power and dependence power in the sector.

The initial CICEs identification process is based on a literature review, while a fuzzy Delphi method (FDM) was used for the screening process of CICEs. Total interpretive structural modelling (TISM) was used to develop contextual relationships among various CICEs. The results of the TISM are used as an input for the matrix of cross-impact multiplications applied to classification (MICMAC) to classify the driving power and dependence powers of the CICEs.

This paper selected 16 CICEs classified in seven dimensions. TISM results and MICMAC analysis show that leadership, as well as climate and culture, are enablers with the highest driving power and lowest dependence powers; followed by information technology. The results of this study indicate that efforts to continuously develop innovation capabilities in the Indonesian manufacturing industries are strongly influenced by their leadership capability, climate and culture, also information technology-related capability.

The framework assessed in this study provides business managers and policymakers to obtain a bigger picture in developing policies with evidence-based strategy and priority in regard to continuous innovation capability.

The results will be useful for business managers and policymakers to understand the relationship between CICEs and identify key CICEs in Indonesia’s manufacturing sectors, which were previously non-existent.

The advancements in internet technologies and the use of sophisticated digital devices in supply chain operations incessantly generate enormous amounts of data, which is termed as big data (BD). The BD technologies have brought about a paradigm shift in the supply chain decision-making towards profitability and sustainability. The aim of this work is to address the issue of implementation of the big data analytics (BDA) in sustainable supply chain management (SSCM) by identifying the relevant factors and developing a structural model for this purpose.

Through a comprehensive literature review and experts’ opinion, the crucial factors are found using the PESTEL framework, which covers political, economic, social, technological, environmental and legal factors. The structural model is developed based on the results of the total interpretive structural modelling (TISM) procedure and MICMAC analysis.

The policy support regarding IT, culture of data-based decision-making, inappropriate selection of BDA technologies and the laws related to data security and privacy are found to affect most of the other factors. Also, the company’s vision towards environmental performance and willingness for material and energy optimization are found to be crucial for the environmental and social sustainability of the supply chain.

The study is focused on the manufacturing supply chain in emerging economies. It may be extended to other industry sectors and geographical areas. Also, additional factors may be included to make the model more robust.

The proposed model imparts an understanding of the relative importance and interrelationship of factors. This may be useful to managers to assess their strengths and weaknesses and ascertain their priorities in the context of their organization for developing a suitable investment plan.

The study establishes the importance of BDA for conservation and management of energy and material. This is crucial to develop strategies for enhancing eco-efficiency of the supply chain, which in turn enhances the economic returns for the society.

This study addresses the implementation of BDA in SSCM in the context of emerging economies. It uses the PESTEL framework for identifying the factors, which is a comprehensive framework for strategic planning and decision-making. This study makes use of the TISM methodology for model development and deliberates on the social and environmental implications too, apart from theoretical and managerial implications.