Analyzing the green innovation practices based on sustainability performance indicators: a Chinese manufacturing industry case

Regional differences, dynamic evolution and trend prediction of green manufacturing development levels in China

Green manufacturing has become a necessary way to promote new industrialization and realize the high-quality development of China's manufacturing industry. Based on the panel data of 30 provinces in China from 2012 to 2022, this paper constructs a comprehensive evaluation index system for the green manufacturing development level and introduces the TOPSIS- Gray correlation method to comprehensively measure the green manufacturing development level of China as a whole and the four major regions in the eastern, central, western, and northeastern parts of the country. The regional differences, distribution dynamics and evolutionary trends of China's green manufacturing development level are also explored with the help of the Gini coefficient, kernel density estimation and Markov chain methods. Research Findings: (1) The green manufacturing development level in China is on an upward trend, with an overall spatial distribution pattern of "East is superior and West is inferior". (2) There are regional differences in the green manufacturing development level in China, and the differences are widening, with interregional differences being the main reason for this overall difference. (3) The country as a whole, the central region and the western region are polarized to varying degrees, with the rest of the country showing an improvement in polarization. (4) Without considering spatial factors, the development of green manufacturing in each province experiences "club convergence" in the short term, and it is difficult to realize rapid development. Considering spatial factors, China's green manufacturing development level is generally characterized by "elevated in proximity to high levels and suppressed in proximity to low levels", and in the long run, it shows a distribution trend toward the concentration of high values. The findings of this study can provide new ideas for promoting synergistic efficient development of green manufacturing in China.

Optimization of the extraction process for Shenshou Taiyi powder based on Box-Behnken experimental design, standard relation, and FAHP-CRITIC methods

BACKGROUND

Ancient classic prescription play a crucial role in the preservation and advancement of traditional Chinese medicine (TCM) theories. They represent a significant milestone in the ongoing development and transmission of TCM knowledge and practices and are considered one of the breakthroughs in the development of TCM inheritance. In the process of developing ancient classic prescriptions, many problems may still arise in ensuring quality consistency between traditional methods and modern production processes, among which the extraction process poses major challenges. This paper introduces a practical approach extracting an ancient classic prescription using a modern extraction process. The technique is demonstrated through the study of the extraction process of Shenshou Taiyi powder (STP).

METHODS

This study focuses on optimising the STP extraction process to ensure consistency in the quality of the product obtained through ancient and modern processes using the standard relation and fuzzy analytic hierarchical process (FAHP) and criteria importance through intercriteria correlation (CRITIC) method integrated weights combined with the Box-Behnken response surface test. Using the contents of rosmarinic acid, isoimperatorin, puerarin, as well as the extract yield and fingerprint similarity as evaluation indexes of STP, the Box-Behnken response surface method was employed to examine the varying extraction parameters, including water addition ratio, extraction duration, and number of extractions. The weighted coefficients for each parameter were calculated by combining the benchmark correlation and FAHP-CRITIC method, deriving a comprehensive score.

RESULTS

The optimal extraction process for STP consisted of a two extractions, each using at a tenfold quantity of water, performed for one hour. Process verification across three separate batches yielded a comprehensive score of 94.7, with a relative standard deviation of 0.76%.

CONCLUSIONS

The application of the Box-Behnken response surface method combined with standard relation and FAHP-CRITIC approach proved to be stable and feasible for optimising the extraction process of STP.

Green transition in the hospitality industry: The influence of market forces and customer dynamics on sustainable performance in the digital era

In recent years, the ongoing environmental challenges have caused hotel firms to experience stress from stakeholders (i.e., customers and competitors). These stringent ecological changes have compelled hospitality firms to go green. This study investigates the influence of customer and competitive pressures on green innovation and sustainability in the hospitality industry. Utilizing a sample of 309 employees from multiple hospitality companies, the study rigorously tests a series of hypotheses using Smart PLS and Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings supported all the hypotheses, indicating that customer and competitive pressures significantly foster green product and process innovations, enhance sustainable firm performance, and encourage green CSR initiatives in the Chinese hospitality sector. Furthermore, green product innovation, green process innovation, and green CSR were found to be critical mediators in enhancing firm performance under the influence of these pressures. These results have substantial implications for theory and practice, highlighting the importance of external pressures in promoting sustainable practices in the hospitality industry.

Effects of environmental awareness training and environmental commitment on firm's green innovation performance: Empirical insights from medical equipment suppliers

In recent years, the intensification of global industrialization coupled with the enterprise's production and operating activities have caused pollution, increasing the current environmental pressure. Relevant government departments in China have instituted several stringent measures (environmental protection sensitization and awareness activities, training sessions, and exchange activities targeted towards enterprise managers) to address these rising environmental problems. Though these measures have gained traction over the years, there is a dearth of research on their effectiveness on the green innovation performance of enterprises. To bridge the gap, this research explores the effect of environmental awareness training, knowledge exchange activities, and commitment on green innovation performance with survey data from 285 medical equipment manufacturing companies in China. It further expands the theoretical application of environmental awareness training, commitment, and innovation performance from the lens of the Knowledge-Based View. The findings depict a positive relationship between environmental awareness training and innovation performance. It also finds a mediating influence of environmental commitment in the relationship between environmental awareness training and green innovation performance. Furthermore, environmental knowledge exchange activities positively moderate the relationship between environmental awareness training and environmental commitment. These findings offer valuable insights for the green development of medical equipment manufacturing enterprises and the government to formulate environmental protection policies.

Unveiling the environmental efficiency puzzle: Insights from global green innovations

The latest surge of global uncertainty and disruptions in global supply networks put policymakers under pressure to emprise green innovations as a vital tool to address environmental concerns. However, producing green innovations doesn't always help in achieving environment-related sustainable development goals. Therefore, in this study, we endeavour to investigate to what extent green innovations are efficient in improving environmental efficiency. To this end, a network bias-corrected data envelopment analysis and clustering analysis is applied. The data used in this study covers 42 countries from different regions, spanning from 2000 to 2020. The results reveal that most countries have not made major advancements in environmental efficiency signifying the low level of green innovations utilization to achieve environment-related sustainable development goals (SDGs). Additionally, the results demonstrate a U efficiency curve for inputs-oriented green innovations efficiency over time, indicating that the initial stages of green innovations production are associated with a decreased return. However, over time, the efficiency exhibits an upward trend. The benchmarking analysis reveals that South American and European Union nations set the bar for other countries in terms of efficiently leveraging green innovations to achieve SDGs. Our findings also suggest that environmental efficiency is more dependent on green-supporting policies such as green energy production and green taxes. As a result, we conclude that achieving environmental SDGs while utilizing green innovations does not always result in the development of other SDGs. Therefore, policymakers need to prioritize pursuing a green developmental approach and supporting policies to achieve environment-related SDGs and other SDGs.

Industry 4.0 impacts on operational and green innovation performances with the mediation of green practices

Purpose

The aim of this study is to investigate how green supply chain management (GSCM) practices mediate the effect of Industry 4.0 technologies on operational and green innovation performances.

Design/methodology/approach

To explore the study, data were collected from 225 different manufacturing industries in Pakistan. Gathered data were used to test the hypotheses using SmartPLS 3 software by using structural equation modeling.

Findings

The findings reveal that operational and green innovation performances are directly affected by the adoption of Industry 4.0 technologies and GSCM practices. Furthermore, the GSCM practices positively affect operational and green innovation performances. The study also investigated that the GSCM practices partially mediate the effect of Industry 4.0 on operational and green innovation performances.

Research limitations/implications

This study has some limitations, the data of this study were majorly collected from large enterprises of Pakistani firms and related to the manufacturing sector only. So, there is a huge need for attention toward small and medium-sized enterprises (SMEs). Very few researchers are focusing on SMEs, so future research can be on SMEs. It can be suggested that the relationship between digital technologies and green innovation performance can be tested through a quantitative procedure. Moreover, the effect of GSCM's aspects can be estimated on manageable execution.

Originality/value

Through the mediating relationship of GSCM practices, this research has made a unique contribution by investigating the influence of Industry 4.0 on operational and green innovation performances. To the author's knowledge, no research has been undertaken in this area.

Green transition in manufacturing: Dynamics and simulation

Under the dual background of global industrial value chain and low-carbon emission reduction, the green transformation and upgrading of the manufacturing industry is an important way to promote production and promote sustainable economic development. Considering that the green transformation of the manufacturing industry is a typical complex adaptation system, based on the intrinsic relationship between the dynamic theory and the green transformation of the manufacturing industry, this paper takes the endogenous variable of the transformation of manufacturing enterprises as the entry point, simulates the transformation of new and old dynamic energy of green transformation, and explores the mechanism of green transformation and upgrading of manufacturing industry and the conversion process. According to the model, it is concluded that the green transformation of manufacturing enterprises is the result of the multi-stage transformation of enterprises. In this process, the change inertia overcomes old dynamic inertia and promotes the new dynamic to gradually replace the old dynamic. At the end of the article, specific suggestions are given to promote the green transformation of manufacturing enterprises from the aspects of ideology, policy support, digital empowerment, financial service guarantee system and communication and cooperation.

Health evaluation and key influencing factor analysis of green technological innovation system

Green technological innovation (GTI) aims to realize management innovation and technological innovation with the goal of protecting the environment. The health model is an important aspect of evaluating whether a system is sustainable. There are few studies on the health of green technological innovation system (GTIS), and almost no indicators to evaluate whether GTIS status is sustainable. Here, we first put forward the concept and framework of GTI health. Drawing on the theoretical analysis of natural ecosystems and commercial ecosystems, a health evaluation index system of GTIS is constructed. Using panel data analysis, the GTI status of 30 provinces in China during 2012-2019 is evaluated, the health index and health grade are calculated, and the key factors affecting GTIS health are determined. Through robustness analysis, the consistency of the research framework is verified and several unique insights into the healthy development of GTIS are presented. The results show that there is heterogeneity in GTIS health grades in different provinces, but health grades of most provinces show upward trends within 8 years. Government funds, foreign direct investment, pollution control investment, green product sales revenue, and green technology trading volume are the foci of healthy improvement of GTIS, and they are all positive indicators.

Revitalization of Chinese's manufacturing industry under the carbon neutral goal

Since the beginning of the Industrial Revolution, the manufacturing industry has been crucial for economic growth. China's manufacturing activity began after China approved and opened legal reform to the rest of the world in 1978. There are usually three stages of development, including the catch-up period. At the same time, they reflect the private economic sector, manufacturing, and foreign exchange industries, and the opening up to the international markets. This advancement comes along with high energy consumption, leading to a high rate of pollution. Therefore, this study provides a detailed overview of the "Made in China 2025" pilot target and implementations of policies to achieve a carbon-neutral goal. We assessed the efficiency of implementing policies in the Chinese manufacturing sector and recommended decision-making policies to achieve the "Made in China 2025" plan and the 2030 carbon-neutral goal. The Quantitative Strategic Programming Matrix (QSPM) and SWOT analysis matrix were used to put forward some development strategies to transform and upgrade China's manufacturing industry by combining relevant strategic theories. This study is significant in terms of energy-saving and carbon emission-reducing policy implementations for the Chinese manufacturing industry. In addition, we suggested some measures to achieve a sustainable environment in line with carbon-neutral policies.

Conceptualising the relationship between green dynamic capability and SME sustainability performance: the role of green innovation, organisational creativity and agility

Purpose

The purpose of this paper is to propose a conceptual framework that establishes the linkages among green dynamic capability (GDC), green innovation (GI), organisational creativity (OC) and organisational agility (OA), which influence small and medium enterprises (SMEs) sustainability performance (SP) in trade and service sectors in Thailand.

Design/methodology/approach

This paper conducts a search of existing literature regarding SMEs SP. A conceptual framework is provided that can be used by SMEs to enhance their SP driving sustainable business growth.

Findings

A framework for SMEs sustainability is proposed, which demonstrates the connection between GDC and SME SP, with GI and OC as mediators and OA as a moderator.

Research limitations/implications

This paper is limited in terms of the scope of SME sustainability in the context of the trade and service sector. Future empirical study should be conducted to validate the proposed framework and hypotheses in this study.

Practical implications

This study forms the basis for the enhancement of SMEs SP in relation to boosting their GDC, GI, creativity and agility.

Originality/value

This paper presents a comprehensive framework that leads to the conceptualisation of SME SP. It will help practitioners and academics to better understand the causes of SMEs SP.

Empirical Analysis of the Impact of Industrial Internet Development Environment on Open Green Innovation of Manufacturing Enterprises

This study aims to expand the research perspective from the micro-enterprise level to the regional environment level to identify changes in the regional industrial Internet environment. The development and application of Industrial Internet technologies formed by these changes have spillover effects on Industrial Internet innovation. Sample data from 30 provinces and big cities of China from 2006 to 2018 were used to verify the network externality characteristics of industrial Internet development. The nonlinear impact of environmental factors, such as the proportion of Internet users and intellectual property protection on the open green innovation of manufacturing enterprises, was investigated through the panel threshold model. Meanwhile, the development level of the industrial Internet in eastern and western China is compared and analyzed. This study contributes to existing knowledge and guides practitioners to help manufacturing organizations develop industrial Internet environments.

China's Jinshan Yinshan sustainability evolutionary game equilibrium research under government and enterprises resource constraint dilemma

This paper is based on analyzing the process of green innovation inspiration and green innovation compensation effect after the implementation of environmental regulations by the Chinese Government. This paper tests the hypothesis using the evolutionary game model and studies the underlying behavioral characteristics of the government, enterprises, and the relevant influencing factors. These influencing factors further aid in examining the evolution law applicable on both sides, which are aligned with the dynamic replication equation and evolutionary equilibrium states under different situations. The key variables used in this study include the concentration of government's environmental regulation, the cost of the regulations, economic penalties, enterprise's green innovation-related income, expenditures, and the enterprise's performance appraisal. Moreover, the results of this study reflect the system stability and equilibrium strategy on the proportion of retained earnings spent by enterprises on green innovation activities and the Government's strict environmental regulations. In the process of game strategy selection between the government and enterprises, the net income and weight of eco-efficiency indicators of the enterprises actively carrying out green innovation activities play a decisive role. Moreover, there should be reduced weight of economic benefits and increase the economic sanctions and innovation subsidies of enterprise pollution behaviors. Furthermore, reduced cost of regulations and innovation expenditures help guide enterprises to rationally allocate superior resources to enhance green enterprise innovation and take the level of innovation to the point that it achieves a win-win green sustainable development of economic performance and environmental performance.

Exploring a Pathway to Sustainable Performance in Manufacturing Firms: The Interplay between Innovation Capabilities, Green Process, Product Innovations and Digital Leadership

In recent years, advancing industrialization and rapid climate change have considerably influenced the global consumption pattern of natural assets. Undoubtedly, this massive utilization of natural resources and hazardous environmental emissions have profoundly curbed the worldwide socio-economic context, substantially causing this ecological burden to amplify the harmful effects on countries’ prosperity. This study aims to improve the sustainable performance of manufacturing firms in Pakistan through innovation capabilities and green process innovation. The study has adopted a quantitative approach, and data has been accumulated through a structured questionnaire distributed among 299 employees working in manufacturing firms. A structural equation model using Smart PLS software was used to analyze the collected data from the respondents. The results have identified a significant correlation between innovation capabilities, green process innovation, and sustainable performance. The buffering role of digital leadership enhances the employees’ creative skills and sustainable performance. Additionally, the extent that green product innovation plays a mediating role between innovation capabilities, green process innovation, and sustainable performance has been contemplated. Henceforth, the current study also analyzes the moderating role of digital leadership in sustainable performance.

Design and Multiobjective Optimization of Green Closed-Loop Manufacturing-Recycling Network Considering Raw Material Attribute

Regarding decision planning in the electronic manufacturing industry, this paper designs a green closed-loop manufacturing-recycling network for multiperiod production planning for multiple products. The network considers the tradeoff between production costs and environmental pollution induced by production scraps. Therefore, a mixed integer programming model with a dual objective is designed to achieve environmental protection and reduce production costs through resource recovery and utilization. At the same time, the recycled materials are considered to be treated, not entirely new, which could affect the manufacturing qualified rate. Thus, material attributes are proposed to distinguish new raw materials from recycled (second-hand) ones through the closed-loop manufacturing-recycling process to enhance the manufacturing qualified rate. In order to solve the dual-objective optimization model and realize optimal decisions, an epsilon constraint is designed to generate a nonextreme solution set by changing the original feasible region. The results show its ability to obtain a more balanced solution in terms of cost and environmental factors compared with the fuzzy-weighted method. Meanwhile, the analysis proves that the dual-objective optimization model with distinguishing material attributes can improve the efficiency of the manufacturing qualified rate and achieve a win-win situation for production and environmental protection during enterprise production.

Decoupling Institutional Pressure on Green Supply Chain Management Efforts to Boost Organizational Performance: Moderating Impact of Big Data Analytics Capabilities

This paper aims to empirically examine the impact of institutional pressure on green supply chain management (GSCM) efforts and the moderating role of big data analytics capabilities (BDAC) on organizational performance. This study greatly develops a research model by integrating institutional theory, the natural resource-based view (NRBV), and dynamic capability theory to explore this relationship. This article is based on structured questionnaire data of 347 supply chain personnel. We employed structural equation modeling to verify the research hypotheses. The findings provide empirical support for institutional pressures affecting GSCM efforts and organizational performance. The results also showed that the moderating effect of BDAC positively strengthened the impact of GSCM effort on organizational performance. The findings extend and refine the existing GSCM literature, providing new insights for scholars to explore this view further. Practitioners can turn their attention to incorporating institutional pressures and advanced technologies into organizational decision-making, even in times of crisis such as Covid-19.

Adoption of innovative strategies to mitigate supply chain disruption: COVID-19 pandemic

COVID-19 pandemic outbreak caused supply chain (SC) disruption and threatened human life across the world, which could be mitigated through innovative strategies. Based on this scenario, this study examines the impact of COVID-19 on green practices, SC crisis mitigation strategies, smart technologies, and sustainable supply chain performance in the Pakistani manufacturing industry. Data was collected from Pakistani firms and employed structural equation modeling for testing hypotheses. The empirical results found that the COVID-19 pandemic is statistically related to green practices, SC crisis mitigation strategies, and smart technologies, while it harms sustainable supply chain performance. Moreover, green practices, SC crisis mitigation strategies, and smart technologies positively contribute to sustainable supply chain performance. The results of this study also confirmed the mediating role of green practices, SC crisis mitigation strategies, and smart technologies and moderating role organizational commitment in the context of a developing economy’s manufacturing industry. This study enhances awareness and understanding and contributes to the existing literature on verifying the link between COVID-19 pandemic and green practices, SC crisis mitigation strategies, and smart technologies to increase sustainable supply chain performance during a pandemic disruption in the Pakistani context. This study supports the managers of supply chain and manufacturing firms in adopting green practices and smart technologies. Also, it helps in the formation and successful implementation of SC crisis mitigation strategies during the crisis.

Environment Sustainability Is a Corporate Social Responsibility: Measuring the Nexus between Sustainable Supply Chain Management, Big Data Analytics Capabilities, and Organizational Performance

Sustainability has profound implications for environmental competitiveness, yet little has been done to study the feasibility of sustainable supply chain management (SSCM) practices as a predictor of organizational performance (operational and environmental performance). By integrating stakeholder theory and dynamic capability theory, this study aims to determine the impact of corporate social responsibility (CSR) on SSCM practices and assess its impact on organizational performance. This research also investigates the role of big data analytical capabilities (BDAC) in mediating the relationship between SSCM practices and organizational performance. The authors collected data online, examined 320 valid responses, and tested research hypotheses. The findings suggest that CSR (both internal and external CSR) positively promotes SSCM practices and contributes to expanding dynamic capacity theory in the context of BDA capabilities. BDAC is also a key mediator between SSCM practices and organizational performance. These results contribute to and improve the research on stakeholder theory and SSCM practice and provide a new perspective for scholars to further study this issue.

Green Supply Chain Management Practices’ Impact on Operational Performance with the Mediation of Technological Innovation

Industries strive to prevent ecologically destructive actions in their supply chains. At the same time, the optimization of their resources is a major concern for industries to minimize carbon emissions, boost sustainable practices, and improve a country’s long-term economic development. Therefore, the objective of this study is to examine the impact of Green Supply Chain Management (GSCM) methods on operational performance with the mediation of technological innovation, in the context of Pakistani manufacturing firms. The partial least square-structural modeling (PLS-SEM) method is adopted in this paper. Data were gathered from 223 different manufacturing firms in Pakistan and then analyzed among these variables. The data show good validity and reliability, and structural model explains 61% of the variance in operational performance and 45.4% of the variance in technical innovation, demonstrating its predictive validity. The R-square criteria classify R-square entities of 0.67, 0.33, and 0.19 as considerable, moderate, and weak, respectively. It is demonstrated that all the f-square values are greater than 0.020 and 0.35, indicating a significant effect on the model’s validity. The findings of this study reveal that GSCM practices have a significantly positive effect on both technological innovation and operational performance. Technological innovation has a direct influence on operational performance and has a partial mediating effect on the relationship between GSCM practices and operational performance. Therefore, this research offers managers insight into the importance of technological innovation and GSCM practice adoption to achieve competitive advantages. It further provides the groundwork for managers, practitioners, and environmental management researchers to emphasize the value of GSCM practice in improving operational performance.

Prioritizing Indicators for Sustainability Assessment in Manufacturing Process: An Integrated Approach

Sustainable manufacturing has renewed attention among researchers to address various sustainability challenges in manufacturing industries. Sustainability assessments of manufacturing organizations help minimize the negative environmental impact and enhance reputation among public and regulatory agencies. To assess the sustainability of the manufacturing process; it is indispensable to investigate the structured set of triple bottom line (3BL) indicators. Moreover, there is no comprehensive and structured set of 3BL indicators that can effectively assess the sustainability of any organization’s manufacturing process. This research aims to identify and prioritize experts’ consensus structured set of 3BL indicators. The 3BL indicators were identified through an open-ended questionnaire. The prioritization was performed through the Best-Worst Scaling (BWS) approach. Further, Multi-Criteria Decision Analysis (MCDA) method was utilized to draw the consensus ranking of sustainability indicators in manufacturing. The findings indicated that the release of greenhouse/harmful gas is the best indicator in the perspective of environmental criteria followed by the rate of contribution to society and operational cost are the most important critical indicator in the case of social and economic sustainability criteria. The outcome of the present study will facilitate researchers and practitioners in developing suitable readiness and operational plans for the sustainability assessment of the manufacturing process.

Promoting sustainability through green innovation adoption: a case of manufacturing industry

Green innovation is becoming more common among researchers and practitioners around the world due to environmental and social issues. Green innovation minimizes wastes and pollution, and also leads to financial gains and better image if implemented effectively. Nowadays, developing countries pay greater emphasis on environmental issues as their manufacturing industries are considered major contributors to pollution. Considering the case of a developing country (Pakistan), the study empirically identified the drivers of green innovation in the manufacturing industry. A hybrid methodology-Fuzzy Delphi method (FDM), interpretive structural modeling (ISM), and cross-impact matrix multiplication applied to classification (MICMAC)-was used to develop a novel framework for analyzing the green innovation drivers. At first, green innovation drivers were selected from past studies; they were further screened by applying Fuzzy Delphi approach. The MICAMAC and ISM results indicate that "cost reduction" and "government support" are the most important drivers motivating green innovation implementation in the Pakistani manufacturing industry, while a green image appeared as the least significant driver of green innovation adoption. The study's findings have significant implications for managers and policymakers to develop green strategies for manufacturing sector.

Sustainable Production Clauses and Positioning in the Global Value Chain: An Analysis of International Investment Agreements (IIA) of the ICT Industry in Developing and Developed Markets

Positioning in the global value chain (GVC) reflects the level and kinds of value creation of a firm or industry. The value creation can be on the upstream or downstream of the value chain. This study explores the effects of sustainable production clauses on the economic and physical positioning of information and communication technology (ICT) firms in the global value chain (GVC). We examined 2107 international investment agreements (IIA), signed by 54 countries that represent 70% of the global investment agreements. The empirical results show that the sustainable production intensity clauses in the IIAs have a significant impact on the positioning of ICT’s in the GVC. However, the degree of impact on the economic scale of participation and physical location in the GVC differs. The heterogeneity test shows that the sustainable production intensity clauses of IIAs between developed and developing countries affect positively and significantly the physical and economic locations in the GVCs. This is less significant while the IIAs are signed between the developed markets. These findings demonstrate that countries should consider sustainable production principles and responsible business conducts while signing the IIAs, and ensure their implementation while participating in the GVCs. This process can enhance value creation by moving towards higher value creation activities within the GVC.

Multidimensional perspective of green financial innovation between green intellectual capital on sustainable business: the case of Pakistan

This study investigates the multifaceted role of green innovation among green intellectual capitals (GICs) on business sustainability in Pakistan's manufacturing sector. A quantitative method based on the SEM model on SmartPLS and Stata analysis was used, which was supplemented by a survey of 800 Pakistani SME sector supply chain-associated participants. The findings revealed a significant effect of green intellectual capital and green innovation on business sustainability, while structural capital was found to have a significant moderating effect on the business sustainability of Pakistani firms. It has been determined that the relationship between GIC and BS has a strong moderation of green innovation. Furthermore, the relationship and impact of GICs on the business sustainability of Pakistani manufacturing companies were statistically significant, and green innovation played a moderating role between GIC and business sustainability. Therefore, it has been suggested that Pakistani manufacturing companies participate in eco-innovation to progress business sustainability.

Knowledge Management in Relation to Innovation and Its Effect on the Sustainability of Mexican Tourism Companies

An essential aspect of today’s companies is to convert their knowledge into innovative applications that have a sustainable effect; therefore, this study focuses on determining the relationship between the three mentioned constructs. To verify this, a questionnaire was applied to 492 companies in the tourism sector in southern Sonora, Mexico, whose information was captured in SPSS and analyzed with structural equations in the SmartPLS software. The main findings affirm that knowledge management has a direct, positive, and significant relationship with sustainability and innovation, as well as a positive and direct relationship between innovation and sustainability. Companies can focus on knowledge management that will generate innovation and in turn will be distinguished by achieving sustainability, with a possible generation of competitive advantage, as well as sustainable innovation.

Leaders’ Support of Sustainable Innovation and Business Sustainability in Developing Countries: Evidence from Small and Medium Food Processing Enterprises

Business sustainability has become obligatory in small and medium enterprises (SMEs). To remain competitive and survive in the market, sustainable innovation is the key. However, SMEs, especially in food processing in emerging markets, still lack resources to become more innovative. The objective of the article is to analyze factors affecting sustainable innovation in food processing SMEs and their impact on business sustainability. Cross-sectional quantitative research builds on a sample of 157 owners of food processing SMEs in Indonesia. The results show that organizational sustainable innovation in food processing SMEs depends on employees’ innovation potential and an organization’s innovation culture; meanwhile, both variables are influenced by leaders’ support of sustainable innovation. Promisingly, organizational sustainable innovation increases business sustainability. Thus, our research highlights the important role of leaders’ support in achieving organizational sustainable innovation and, finally, long term business success. Furthermore, this study uncovers the underlying mediatory mechanisms, which deepen our theoretical understanding and guide practitioners with a concise and comprehensive framework for sustainable innovation in SMEs.

The role of emerging technologies in implementing green practices to achieve sustainable operations

Purpose

The current study investigates the effect of industry 4.0 on green practices, including green manufacturing and green logistics, in the context of emerging economies.

Design/methodology/approach

A cross-sectional data were collected from 234 manufacturing firms in Pakistan, and PLS-SEM was employed to test hypotheses.

Findings

With the advent of industry 4.0 in the current era, more emphasis is being given to the adoption of digital technologies in every field. The adoption of the green approach in supply chain management provides firms with socioeconomic and environmental benefits. The study results indicate that industry 4.0 positively affects green practices, including green manufacturing and green logistics. Moreover, the results also illustrate that these green practices have a substantial effect on the sustainability performance of the firms.

Research limitations/implications

This study provides an amplified understanding of the industry 4.0 technologies in the adoption of green practices. The outcomes also offer a policy framework for managers, legislators and manufacturers to promote green practices (i.e. green manufacturing and green logistics) in businesses.

Originality/value

Although several recent studies have tried to investigate the effect of green practices on sustainability performance. However, as per the author's best knowledge, very few studies have analyzed the influence of industry 4.0 on green practices (i.e. green manufacturing and green logistics) in the context of emerging economies.

A multi-stage fuzzy decision-making framework to evaluate the appropriate wastewater treatment system: a case study

Selection of appropriate treatment processes for wastewater treatment (WWT) plants at the design stage involves a careful examination of different economic, environmental, and social parameters. Designers and decision-makers seek a compromise among such conflicting elements, which can be facilitated by decision support tools that are adapted for the ambiguity of individual opinions and decision parameters. This study aims to improve the qualification and efficiency of decision-making in WWT processes. A multi-stage framework is proposed to help select investments, technology, appropriate technology-specific system, and companies that apply such systems. The framework combines the Analytic Hierarchy Process (AHP), Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE), cash flow analysis, and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) within fuzzy logic. The main contribution is the description and formation of an integrated framework to guide businesses and researchers for the evaluation of several WWT decision processes. To the best of the authors' knowledge, no study in the literature fuses multiple stages of this WWT process with the proposed approaches.