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The study assessed the mediating role of green organizational capabilities (green technology development, green operations, and green transactions), in the relationship between green value co-creation and organizational resilience among Chinese manufacturing firms, that is, firms' ability to build strong organizational resilience in response to the COVID-19 pandemic. It focused on manufacturing firms operating within Shenzhen, a coastal city located within the Guangdong province in southeastern China. The sample comprised 234 firms. Data were analysed using a covariance-based structural equation modeling. Findings revealed that green value co-creation had no direct effect on organizational resilience, rather, its effect was realized indirectly through green organizational capabilities. The study concludes that manufacturing companies can augment their organizational capabilities by leveraging the knowledge of their customers through green value co-creation to build strong organizational resilience. Theoretical and managerial implications have been provided.
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Concerns about the effects of global warming and predicted rising sea levels are radically changing government policies to lower carbon emissions using sustainable green technologies. The United Kingdom aims to reduce its carbon emissions by 78% by 2035 and achieve net zero by 2050. This is a major driver for energy management and is influencing development of buildings which use autonomous smart technologies to assist in lowering carbon footprints. These Smart Buildings use digital technologies by connecting sensor data with intelligent systems which can be monitored remotely to provide more efficient facilities management. The data harvested and transmitted from the IoT sensors provides a key component for Big Data Analytics using techniques such as Association rule mining for intelligent interpretation which can assist facilities management becoming more agile regarding office space utilization. The shift toward hybrid working particularly instigated by the COVID-19 pandemic and recent energy supply concerns caused by the Ukraine crisis presents facilities management with opportunities to optimize their space, reduce energy consumption, and allow them to identify commercial opportunities for the unused space throughout the building. This chapter discusses the use of association rules for data mining derived from a simulated dataset for an investigative analysis of office workflow patterns for facilities management operations, resource conservation, and sustainability. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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After COVID, Original equipment manufacturers (OEMs), suppliers, and distributors are seeking to streamline their local, and global supply chains, the issue has gained attention in how they identify, analyze and manage their procurement and supply chain processes with stakeholders. The use of supply chain adoption with green technology has been found to be preferred in international trade, which is forcing the Indian manufacturing, and services sector to realign their CSR (Corporate social responsibility) goals. Interviews have been conducted with a mix of manufacturing and service firms in India to map their sustainable procurement in green supply chain practices. The use of MAXQDA software for conducting thematic analysis to support the inductive theory and trend-building practices to know "what, why, and how” from interview responses. Each sector, manufacturing, and service showed distinct trends that divorce their approach to green SCM, and supply chain strategy for sustainable procurement though they have spread awareness about sustainable procurement with stakeholders, emphasizing economic benefits. Additionally, they pursued jointly to address environmental issues and extend societal benefits as a CSR effort. Variances in approaches in manufacturing are market-linked, time-based, and demand-driven while services firms showed green technology pledges as CSR initiatives along with an environmental emphasis in downstream SCM activities. © 2023 K.J. Somaiya Institute of Management Studies and Research.
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University students are regarded as a readily available market segment for public transport. In Hanoi, as elsewhere, they constitute a large portion of bus passengers. However, one portion has been quitting buses, and the reasons were so far unknown. Nor was it clear whether they planned on retuning. Through a survey of more than 800 students in seven higher education institutions, this study aimed to find the answers to these questions. The study revealed that bus ridership was determined by socio-demographic variables (year of studies, household income, employment status, motorcycle ownership), environmental variables (home-university distance), and psychological variables (convenience, bus staff behaviour, risk of sexual harassment, reliability and health, image and status). A negative disruptor such as the fear of Covid-19 infection had little effect on the decision to continue riding buses. Meanwhile, the prospect of riding 'clean and green' electric buses, which were introduced in a pilot program, was a positive disruptor that may lead a portion of students to return to public transport.
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This paper addresses the impact of the Covid-19 lockdown on the warehousing of perishable items facing demand-side shocks, mainly those with selling price and product quality dependent demand, for example, fresh fruits, meats, vegetables, packed foods, etc. Along with demand-side issues, such an inventory system consumes a significant amount of energy in terms of freshness, increasing carbon tax and dwindling the firm's total profit. We formulate two-warehouse inventory models of perishables items using the first-in-first-out (FIFO) dispatching policy under two different Covid-19 lockdown scenarios. The two-warehouse system primarily consists of an owned warehouse (OW) and a rented warehouse (RW). Two different lockdown scenarios are considered as;(i) the lockdown during the consumption of goods in OW and (ii) the lockdown during the consumption of goods in RW. The demand rate is assumed to decline and surge by a finite volume as lockdown is forced and relaxed. The proposed models help in assessing the impact of lockdown on (i) product quality, (ii) product cost, (iii) inventory level, (iv) freshness keeping efforts, (v) investment in green technologies, and (vi) carbon cap and trade policy. We determine the above six parameters to maximize the firm's total profit. The key findings of this model suggest that yield is primarily affected due to carbon cap and trade policy, lockdown period, item price, backlogging, and variation in the holding costs in OW and RW. These models may assist the small, medium, and large firms involved in perishable or cold supply chains to assess the effect of Covid-19 like disruption and take corrective measures to maximize their profit.
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The growth of green-oriented businesses for sustainable development (SD) is no longer optional in the current dynamic world, especially for manufacturing businesses in general. Accordingly, the present study investigates the interlinkages between green organizational strategy (GOS), environmental corporate social responsibility (ECSR), and organizational sustainable performance (OSP) by exploring the key mediating role of green technology innovation (GTI). This study uses a quantitative method to gather data from Chinese manufacturing industries, employing a well-structured questionnaire. Senior and middle-level managers were the intended respondents. From the primary survey, 264 valid responses were gathered. The final data were analyzed using SmartPLS (version 3.3.9) by adopting structural equation modeling (SEM) to examine the associations between the targeted constructs, and the results add to the recent literature by offering a cohesive model of GOS, ECSR, GTI, and OSP. The findings revealed that GOS has a strong positive effect on ECSR, GTI, and OSP. Further, ECSR has a strong positive impact on GTI and OSP. Meanwhile, GTI is a key mediating variable in these relationships, which previous studies have not explored. This study innovatively integrates the three green traits, namely, GOS, ECSR, and GTI, into a comprehensive model that is understudied in existing literature in order to help businesses improve their sustainable competitive advantage. The ultimate aim is to help businesses improve their environmental performance and achieve solid sustainability over the long term. Copyright © 2022 Ye, Hao, Shahzad and Kamran.
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Carbon and Sulfur dioxides emissions are the key issues of global warming that affects on human health. Emissions cap- and -trade policy is a key mechanism implemented in several countries to reduce the emissions. Nowadays, public gathering is restricted due to the pandemic situation caused by COVID-19. As a result, people are facing huge problems in their regular activities and lifestyle. During the lockdown periods, demands for few merchandises decrease and the deterioration rate increases. Moreover, because of the unavailability of raw materials and labours during the lockdown, shortages occur at the manufacturing company. Keeping these problems in mind, a multi-objective sustainable economic production quantity model is proposed with partially back-ordering shortages, in which the effects of sustainability are investigated. To handle the demand fluctuation throughout the current pandemic, emergency level dependent demand rate is assumed. To reduce greenhouse gases emissions and deterioration rate, investments in green technology and preservation technology efforts are used. The objectives of this study are to maximize the manufacturera s profit and minimize the greenhouse gases emissions for producing green products. The multi-objective model is solved by utilizing the fuzzy goal programming approach. The mathematical model is illustrated by four numerical examples. The main finding of the work is that under both green and preservation technologies investments, a sustainable model with partially back-ordering shortages and lockdown level dependent demand rate decreases justifiable greenhouse gases emissions and increases the producta s greening level. The results indicate that the system profit is increased by 16.1% by investing in both preservation and green technology. Furthermore, a sensitivity analysis is performed along with some managerial insights for practitioners. Finally, the paper is ended with conclusions and future research tips. ©
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The COVID-19 pandemic has created multiple problems in the existing transportation system. The contribution of this study is to guide logistics managers as they make ordering decisions within a disrupted transportation system. In the overall supply chain system, inventory decisions have been either compromised or challenged. Traditional inventory decisions that consider preplanned transportation facilities (and speeds) are currently becoming obsolete, predominantly in post-COVID times due to delays in the delivery of products and higher delivery costs. Therefore, businesses such as retailers must align ordering and pricing decisions to maintain a sustainable profit. To address this issue, this study investigates optimum inventory decisions under the pandemic's effects while considering the transportation cost as proportional to COVID-19 intensity. This study also considers product deterioration, time-dependent holding costs, price-dependent demands, and carbon emissions from vehicle operation and intends to establish a harmonious relationship among these attributes. The optimization of green technology investment is studied to reduce emissions due to transportation. Some theoretical derivations and numerical examples are given, and they are followed by a sensitivity analysis to extract important managerial insights into the effect of COVID-19. The manager can set an optimal selling price and the cycle length by carefully planning the number of trips in considering the rate of the outbreak and its effect on the increasing transportation cost.
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This review gives concise information on green technology (GT) and Industrial Revolution 4.0 (IR 4.0). Climate change has begun showing its impacts on the environment, and the change is real. The devastating COVID-19 pandemic has negatively affected lives and the world from the deadly consequences at a social, economic, and environmental level. In order to balance this crisis, there is a need to transition toward green, sustainable forms of living and practices. We need green innovative technologies (GTI) and Internet of Things (IoT) technologies to develop green, durable, biodegradable, and eco-friendly products for a sustainable future. GTI encompasses all innovations that contribute to developing significant products, services, or processes that lower environmental harm, impact, and worsening while augmenting natural resource utilization. Sensors are typically used in IoT environmental monitoring applications to aid ecological safety by nursing air or water quality, atmospheric or soil conditions, and even monitoring species' movements and habitats. The industries and the governments are working together, have come up with solutions-the Green New Deal, carbon pricing, use of bio-based products as biopesticides, in biopharmaceuticals, green building materials, bio-based membrane filters for removing pollutants, bioenergy, biofuels and are essential for the green recovery of world economies. Environmental biotechnology, Green Chemical Engineering, more bio-based materials to separate pollutants, and product engineering of advanced materials and environmental economies are discussed here to pave the way toward the Sustainable Development Goals (SDGs) set by the UN and achieve the much-needed IR 4.0 for a greener-balanced environment and a sustainable future.
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Despite the impact of the Covid-19 pandemic on social activities and the global economy, the investment enthusiasm for green transformation in various countries has still been active. In fact, most countries have launched “green recovery” plans after 2020. Green technology innovation has attracted much attention, and many countries have introduced a series of subsidy policies to support green technology innovation transformation (GTIT). This study first discusses the influence of government subsidies on the GTIT of Chinese enterprises by using the manual collection and sorting of data concerning environmental protection subsidies, R&D subsidies, and talent subsidies, and the effects of these subsidies on different enterprises are analyzed. Empirical results show that environmental protection subsidies, R&D subsidies, and talent subsidies can significantly promote GTIT, and the effects of these subsidies on the GTIT of different enterprise are heterogeneous. The environmental protection subsidies, R&D subsidies, and talent subsidies have significant positive impacts on the GTIT of non-state-owned enterprises (non-SOEs) and high asset–liability-ratio enterprises. In contrast, only environmental protection and talent subsidies have significant positive effects on the GTIT of enterprises with low asset–liability-ratio. Environmental protection subsidies, R&D subsidies, and talent subsidies will promote the enterprises to increase their R&D investment, therefore enhancing their GTIT. Our research distinguishes the types of government subsidies for the first time and analyzes their impacts on different enterprises, which will be helpful for governments to improve relevant policies.
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Covid is giving us many lessons among which one must be to realize that this is the time to act for sustainable future. The smart world around us has made it inevitable to have an alarming situation regarding the uncontrolled growth of waste products such as plastic and electronic wastes. Both are immense threats to the health of human, wildlife and environment, that eventually affect the societal and economic structures as evident from recent Covid-crisis. The proper management of these wastes and innovating ideas for new sustainable technologies are the need of the hour. Circular economy act with green technology (green economy) is the way to tackle this challenge. Current perspective presents the overview of the scenario regarding these burgeoning issues and demonstrates some measures that are taken or being considered to depend on to come out of them.
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Purpose: This paper aims to investigate the impact of supply chain disruptions on the operations and sales performance of micro, small and medium enterprises (MSMEs) and the adoption of “green” technology during the COVID-19 pandemic in Davao Region, Philippines. Design/methodology/approach: A business impact survey was conducted among 113 MSMEs in Davao Region through the Regional Inclusive Innovation Center participated by the industry, government and the academe from October–December 2020. The impact of supply chain disruptions on the status of business operations was determined using ordered logit regression, while the impact on sales performance during the lockdown and new normal periods were modeled using logit regression. The technology upgrading plans of the MSMEs, including the adoption of “green” technology, were also determined. Findings: This study found that the extent of disruption in processing the goods and services resulted in a negative impact on business operations, and the disruption of the availability of raw materials negatively affected the sales performance during the lockdown period. Moreover, around 20%–33% of MSMEs experiencing heavy supply chain disruptions had a plan to upgrade their business processes by adopting “green” technology. Research limitations/implications: MSMEs need to establish strategic collaboration among the different stakeholders through public, private, non-government institutions and academe collaboration to enhance the capabilities of MSMEs in handling supply chain disruptions and pursuing technology upgrading. Originality/value: This paper is among the early studies of the impact of COVID-19 to supply chains in the Philippines focusing on the MSMEs. © 2021, Emerald Publishing Limited.
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It has been proven that rapid bioinformatics analysis according to patient health profiles, in addition to biomarker detection at a low level, is emerging as essential to design an analytical diagnostics system to manage health intelligently in a personalized manner. Such objectives need an optimized combination of a nano-enabled sensing prototype, artificial intelligence (AI)-supported predictive analysis, and Internet of Medical Things (IoMT)-based bioinformatics analysis. Such a developed system began with a prototype demonstration of efficient diseases diagnostics performance is the future diseases management approach. To explore these aspects, the Special Issue planned for the nano-and micro-technology section of MDPI's Biosensors journal will honor and acknowledge the contributions of Prof. B.D. Malhotra, Ph.D., FNA, FNASc has made in the field of biosensors.