Governance pressures and performance outcomes of sustainable supply chain management – An empirical analysis of UK manufacturing industry

Although sustainable supply chain management (SSCM) has recently received increasing attention among UK manufacturing firms, there is a concern as to whether SSCM practices are being implemented because they are profitable or only because of governance coercive pressure. Thus, the aims of this paper are twofold: first, determining the role of governance in the adoption of SSCM practices; second, investigating whether SSCM practices can be both environmentally beneficial and commercially viable. In light of these issues, this paper develops and empirically assesses an integrated model of governance pressures-SSCM practices-performance. Data was collected from 146 UK manufacturing managers, and analysed using the structural equation modelling method. Exogenous driving forces of governance were found to be precursors to the successful implementation of SSCM practices. The empirical results further suggest that while the implementation of sustainable supply chain management has a positive effect on environmental performance, it does not necessarily lead to improved economic performance, as only sustainable procurement was found to have a positive effect on economic performance. This paper contributes to the literature by highlighting the role of governance in SSCM adoption and performance gains in environmental protection while economic performance is partially compromised. The results also provide useful insights for both managers seeking to adopt sustainable practices and policy-makers seeking to further promote sustainable supply chain

Forecasting carbon price using empirical mode decomposition and evolutionary least squares support vector regression

Conventional methods are less robust in terms of accurately forecasting non-stationary and nonlineary carbon prices. In this study, we propose an empirical mode decomposition-based evolutionary least squares support vector regression multiscale ensemble forecasting model for carbon price forecasting. Firstly, each carbon price is disassembled into several simple modes with high stability and high regularity via empirical mode decomposition. Secondly, particle swarm optimization-based evolutionary least squares support vector regression is used to forecast each mode. Thirdly, the forecasted values of all the modes are composed into the ones of the original carbon price. Finally, using four different-matured carbon futures prices under the European Union Emissions Trading Scheme as samples, the empirical results show that the proposed model is more robust than the other popular forecasting methods in terms of statistical measures and trading performances

Effects of public funding on the commercial diffusion of on-site hydrogen production technology: A system dynamics perspective

As the prospect of the fuel cell electric vehicle (FCEV) market is uncertain, the effects of government subsidies on the commercial diffusion of hydrogen production infrastructure will need to be effectively evaluated to help policymakers decide how they should financially support the development of future hydrogen technologies. Currently, there is a high intermediate cost in the supply chain of centralized hydrogen production. Decentralized on-site hydrogen production technology is an effective alternative method that can guarantee the operation of hydrogen refueling stations and has been attracting more and more attention from the public. In this paper, which is based on market data from California, we build a system dynamics model to simulate the feedback mechanism of the effects of public funding on the commercial diffusion of on-site hydrogen production technology. The insights derived from the simulation of our system dynamics model suggest that: (1) moderate public funding can help establish the scale of application of on-site hydrogen production technology in the early stages of market development and also provide buffer time for technology upgrading; (2) the adoption of large on-site hydrogen refueling stations is a feasible approach to shorten the standstill period; and (3) excess levels and periods of subsidies would stagnate the growth of supply and demand. We conclude with a discussion about the relevant policy implications from these findings

Strategic resource decisions to enhance the performance of global engineering services

This paper extends our understanding of the internationalisation and firm performance (I-FP) relationship of service firms by considering the influence of strategic decisions on three types of slack resources. The research focusses on an important type of service operations − global engineering services, which are a major part of the global economy and represent a distinctive business model in the contemporary business environment. In doing so, we theorise the I-FP relationship by addressing the knowledge-intensive, project-based and people-centric features of engineering service firms (ESFs); and test the relationship with a carefully assembled dataset containing 12 years’ data from 242 ESFs. We identify a negative overall I-FP relationship, i.e. ESFs’ international expansion leads to worse financial performance in general. The presence of slack resources explains why such a result exists. Our findings have significant implications, both for future research on internationalisation and performance and for firms to effectively deploy their resources to support global service operations in a strategic manner

Involving online community customers in product innovation: The double-edged sword effect

Existing research in the field of business has generated differing views on the relationship between customer involvement and firms' product innovation. Drawing from their findings, some researchers have presented a positive assessment of customers' utility in product innovation, while others have provided a nonsignificant or even negative assessment of customers' usefulness in this area. This paper reconciles these different views by demonstrating that there exists a nonlinear relationship between customer involvement and firms' product innovation performance. To arrive at this conclusion, we use survey data from Chinese manufacturing firms and their online community customers, as well as objective data from the Chinese technology firm Xiaomi, to empirically test our hypothesized nonlinear relationship theory. The results of analyzing the two datasets demonstrate that there is an inverted U-shaped relationship between online customer involvement and firms' product innovation performance. Additionally, we find that customer online community affiliation moderates this relationship; specifically, for low or moderate levels of customer involvement, customer online community affiliation strengthens the positive online customer involvement–product innovation performance relationship, while for high levels of customer involvement, such customer affiliation weakens the positive impact of online customer involvement on firms' product innovation performance. Furthermore, we also show that the factor “customer online knowledge contribution” mediates the relationship between customer involvement and product innovation performance. Overall, this study provides new empirically-supported insights into the impacts of customer involvement and the contribution of customer knowledge through online communities on firms’ product innovation performance, thereby adding significant findings to the literature, as well as offering practical implications to firms regarding how they can best involve online customers in product innovation to achieve the most effective performance

Do environmental subsidies spur environmental innovation? Empirical evidence from Chinese listed firms

Although one of the main reasons why governments offer environmental subsidies to firms is to encourage environmental innovation, the effectiveness of such measures is unclear. In this study, we examine the effects of subsidies on firms’ environmental innovation activities (i.e. environmental technology innovations and environmental management innovations). We use fine-grained panel data on Chinese listed manufacturing companies over the period 2011–2015. We find that whilst Chinese government environmental subsidies boost firms’ environmental management innovation significantly, their effect on environmental technology innovations is not statistically significant. We employ an instrumental variable two-stage least squares (IV-2SLS) approach to handle potential selection bias. We find also that there is no statistically significant relationship between firms’ environmental management innovations and environmental technology innovations. These findings hold for a range of robustness tests

Air pollution and tourism development: An interplay

We empirically examine the interplay between air pollution and tourism development based on a fine-grained dataset covering monthly-level tourism information of 58 major cities in China from October 2013 to December 2017. We adopt an empirical strategy utilizing wind speed as an instrumental variable for air pollution to deal with the endogeneity caused by the reverse causality. We control for individual city fixed effects, month fixed effects, meteorological conditions and other social factors of tourism destinations. We find the interplay between air pollution and tourism development. Our study offers significant empirical evidence for policy makers to design policies that can mitigate the consequences of air pollution in the tourism sector and manage the development of the tourism economy

Narrowing the age-based digital divide: Developing digital capability through social activities

Healthcare information technologies (HIT) have shown great potential for improving the effectiveness and quality of healthcare services. However, the inequal ability of older adults to use HIT may limit their exploitation of these benefits. To narrow the age-based “digital divide”, this research further develops the concept of digital capability and emphasises the link between older adults and their social context. Based on a qualitative inductive study of 33 participants, who included Chinese patients and their family members, we generate a novel theoretical model for understanding the process by which social activities may shape older adults' digital capabilities. Based on the model, we suggest two strategies that might encourage older adults to engage with HIT. This research contributes to the information systems (IS) literature by strengthening digital capability as a conceptual lens to investigate individuals' engagement with information communication technologies (ICTs). It also extends research on the social context for ICT use by revealing how social processes at multiple levels influence digital capability development. Finally, this study offers practical implications for governments and private sectors to encourage and promote ICT use by older adults

A random intuitionistic fuzzy factor analysis model for complex multi-attribute large group decision-making in dynamic environments

The challenge of complex multi-attribute large group decision-making (CMALGDM) is reflected from three perspectives: interrelated attributes, large group decision makers (DMs) and dynamic decision environments. However, there are few decision techniques that can address the three perspectives simultaneously. This paper proposes a random intuitionistic fuzzy factor analysis model, aiming to address the challenge of CMALGDM from the three perspectives. The proposed method effectively reduces the dimensionality of the original data and takes into account the underlying random environmental factors which may affect the performances of alternatives. The development of this method follows three steps. First, the random intuitionistic fuzzy variables are developed to deal with a hybrid uncertain situation where fuzziness and randomness co-exist. Second, a novel factor analysis model for random intuitionistic fuzzy variables is proposed. This model uses specific mappings or functions to define the way in which evaluations are affected by the dynamic environment vector through data learning or prior distributions. Third, multiple correlated attribute variables and DM variables are transformed into fewer independent factors by a two-step procedure using the proposed model. In addition, the objective classifications and weights for attributes and DMs are obtained from the results of orthogonal rotated factor loading. An illustrative case and detailed comparisons of decision results in different environmental conditions are demonstrated to test the feasibility and validity of the proposed method

Energy consumption in the transportation sectors in China and the United States: A longitudinal comparative study

Using Tapio elastic analysis, the differences and similarities of the energy consumption in the transportation sectors in China and the United States were compared. The results showed that the energy consumption of the transportation sectors in the two countries in 2000–2015 had a weak decoupling overall from economic growth in the long term. The decoupling indicator (0.61) in China was about ten times that (0.069) of the United States. Namely, the dependence of China's transportation sector on energy consumption was far larger than that of the United States. Furthermore, using a logarithmic mean Divisia index (LMDI) model, the factors influencing the energy consumption in transportation sectors in China and the United States were analyzed from five perspectives. Based on this model, the reason why the two countries show decoupling difference was explained. Relevant policies implications for energy conservation and emission reduction in the transportation sector were discussed