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This study aims to investigate the antecedents and consequences of green packaging behavior (GPB). A conceptual model has been developed wherein green packaging awareness (GPA) and green packaging initiatives (GPI) are precursors of GPB, and environmental concern and availability of various green packaging alternatives are moderators. The outcomes of GPB in terms of environmental and personal benefits are examined.

Unlike most papers focusing on green packaging from a marketing perspective, this study explores the behavior of rural households from 47 villages in southern India. A carefully crafted survey instrument was developed, and data were collected from 395 respondents. After checking the instrument’s psychometric properties, the results were analyzed using Hayes’s PROCESS macros.

The results indicate that GPA and GPI are positively associated with GPB, GPA predicts GPI, and GPI mediates the relationship between GPA and GPB. Furthermore, findings suggest that environmental concern moderates the relationship between GPI and GPB, and the three-way interaction between the availability of green packaging (second moderator), environmental concern (first moderator), and GPI influences the GPB. Moreover, the outcomes of GPB in terms of environmental and personal benefits are established.

This research has several theoretical implications. It documents that individual awareness of green packaging is a precursor to GPB. This study focused on the rural population from a developing country (India) and hence may suffer from a lack of generalizability across developed nations. However, the results could be generalizable across other developing nations worldwide.

This study motivates individuals to engage in proenvironmental behavior. Moreover, it highlights the importance of GPB in deriving environmental and personal benefits. It is also equally crucial for individuals to engage in proper waste management practices so that the environment is not polluted.

The findings from this research are helpful to society as it focuses on the proenvironmental behavior of individuals. Particularly concerning packaging, this study points out that buying products with green packaging and reusing and recycling such packages is essential to protect the environment.

This study fills the gaps in the literature by focusing on the GPB of the rural population. To the best of the authors’ knowledge, the moderated-mediation model developed and tested in this research is the first of its kind and thus makes a significant contribution to the literature on green packaging and waste management.

The purpose of the study is to explore, with anchorage in theories about the normalization of corruption, under what conditions blockchain technology can mitigate corruptive practices of multinational enterprises (MNEs) in emerging markets (EMs).

By synthesizing a technological perspective and theory on corruption, the authors examine the feasibility of blockchain for fighting corruption in MNEs’ business operations in EMs.

Blockchain technology is theorized to have varying mitigating effects on the rationalization, socialization and institutionalization of corruption. The authors provide propositions describing the effects and the limitations of blockchain for mitigating corruption in EMs.

This paper offers a perspective for how to tackle acute business problems and social problems pronounced in international business but also prevailing elsewhere.

The study contributes to literature in international management by systematically exploring how and under what conditions blockchain can mitigate the normalization of corruption.

This article studies the role played by sustainability operations management (OM) practices in the relationship between governance and environmental and social performance adopting the lenses of the upper echelons theory and the resource-based view. In particular, the authors study three main relationships: (1) the impact of governance on the implementation of sustainability OM practices, (2) the impact of sustainability OM practices on sustainability performance and (3) the mediating role of sustainability OM practices in the relationship between governance and sustainability performance.

To test this study’s research model, the authors retrieved secondary data of 430 firms from the United Stated (US) and Europe and analyzed it using partial least squares (PLS)-based structural equation modeling (SEM).

This study’s results suggest that sustainability OM practices are needed to achieve higher social and environmental performance outcomes from governance, highlighting the key role of the OM department in the achievement of a sustainability strategy.

This paper adopts the environmental, social, governance (ESG) neglected focus and aims to provide a better understanding of and reveal the interrelationship between governance and sustainability OM practices (i.e. environmental and social).

Congruent with the world-wide call to combat global warming concerns and advance intellectual capital (IC), organisations are being pressured to ensure that IC is managed effectively to encourage green initiatives. In this regard, green entrepreneurial orientation (GEO) is emerged as a relevant IC. GEO is recognised as a mitigating factor of environmental degradation in the literature. Although prior literature has observed the nexus between GEO and firm performance, the role of GEO in leveraging sustainable performance has been limitedly explored. This study explored the relationship between IC as a GEO and enterprises' sustainable performance through the moderating roles of environmental consciousness and green technology dynamism (GTD) in the context of two developing countries (Pakistan and Malaysia).

Data provided by 296 respondents from 264 manufacturing small and medium-sized enterprises (SMEs) in Pakistan and Malaysia were analysed through a three-wave research design. AMOS 23 software was used to perform covariance-based structural equation modelling (CB-SEM), while hierarchical regression analysis was applied using the SPSS 25 software to examine the causal relationships in the model.

IC as a GEO significantly influences sustainable performance, akin to environmental consciousness and GTD. Besides, GTD has a significant moderating effect between GEO and financial and environmental performance in Pakistan and Malaysia but not between GEO and social performance. Environmental consciousness has a significant moderating role in the impact of GEO on financial performance in Pakistan and Malaysia, but not on social and environmental performance.

The study's findings are useful for managers of Pakistani and Malaysian manufacturing SMEs to identify ways to encourage GEO to improve sustainable performance in their firms. The findings suggest that managers should effectively implement GTD and environmental consciousness to strengthen the GEO and sustainable performance relationship. Managers can use GEO concretely as a reference for the companies that intend to support the United Nation SDG-2030 agenda and to find new business opportunities for the implementation of sustainable development.

To the best of the authors' knowledge, this study is the first to examine the link between GEO and sustainable performance in developing countries such as Pakistan and Malaysia. Although the influence of various intangible assets or IC on sustainable performance has been widely examined in the literature, the role of GEO as IC has been limitedly explored. This study extends the literature by adding to the knowledge of GEO as a form of firms' IC that enhances boundary conditions in developing countries.

This study aims to identify informal institutions for bottom-of-the-pyramid (BoP) business models in the agricultural sector through the case study of banana growers’ cooperatives.

A case study of six banana cooperatives from Colombia was conducted. The research followed a mixed design, using both qualitative and quantitative data and the application of structural equations.

This study shows that social capital, networking and alliances are essential in BoP businesses.

Authors defined a model of informal institutional factors for the generation of economic and social value in inclusive business, using the new institutional theory and the conceptual development of BoP in agri-business.

The purpose of this paper is to provide the theoretical insights with regard to the green purchasing intention–behavior gap and the role played by social media influences in abating this gap. This paper takes into consideration a wider aspect with regard to the antecedents of behavioral intention through personal and social identities in place of the antecedents presented in the theory of planned behavior and social-identity theory. Furthermore, as the theories lack an explanation of how to reduce the intention–behavior gap, this paper also argues the source credibility model (SCM) in explaining the impact that social media influences can have on the behavioral gap.

Hypothetical deductive method is proposed for this concept paper under the positivism research paradigm.

Not applicable as this is a concept paper. However, the paper discusses the theoretical and managerial implications.

This is a concept paper. Yes this paper discusses the theoretical, managerial, and social/ecological implications.

This paper highlights the relevance of consumers' personal and social identities when consumers make purchasing decisions regarding green products. How managers can make marketing strategies, based on credibility model, involving social media influences as product endorsers and ambassadors, as well as the policy makers to design products, earmark consumer behavior and to conduct marketing campaigns in time to come.

As to how policies can be designed and adopted for bio-based economies where sustainability and circularity are given priority and to increase the attention of businesses moving toward sustainable practices.

Original thought developed based on research, theoretical and market gaps.

Under the constraints of given passenger service level and coupling travel demand with train departure time, this study optimizes the train operational plan in an urban rail corridor to minimize the numbers of train trips and rolling stocks considering the time-varying demand of urban rail passenger flow.

The authors optimize the train operational plan in a special network layout, i.e. an urban rail corridor with dead-end terminal yard, by decomposing it into two sub-problems: train timetable optimization and rolling stock circulation optimization. As for train timetable optimization, the authors propose a schedule-based passenger flow assignment method, construct the corresponding timetabling optimization model and design the bi-directional coordinated sequential optimization algorithm. For the optimization of rolling stock circulation, the authors construct the corresponding optimization assignment model and adopt the Hungary algorithm for solving the model.

The case study shows that the train operational plan developed by the study's approach meets requirements on the passenger service quality and reduces the operational cost to the maximum by minimizing the numbers of train trips and rolling stocks.

The example verifies the efficiency of the model and algorithm.

This paper aims to adapt and computerize the Trail Making Test (TMT) to support long-term self-assessment of cognitive abilities.

The authors propose a divide-and-combine (DAC) approach for generating different instances of TMT that can be used in repeated assessments with nearly no discernible practice effects. In the DAC approach, partial trails are generated separately in different layers and then combined to form a complete TMT trail.

The proposed approach was implemented in a computerized test application called iTMT. A pilot study was conducted to evaluate iTMT. The results show that the instances of TMT generated by the DAC approach had an adequate level of difficulty. iTMT also achieved a stronger construct validity, higher test–retest reliability and significantly reduced practice effects than existing computerized tests.

The preliminary results suggest that iTMT is suitable for long-term monitoring of cognitive abilities. By supporting self-assessment, iTMT also can help to crowdsource the assessment processes, which need to be administered by healthcare professionals conventionally, to the patients themselves.

Exploring the influencing factors on urban rail transit (URT) ridership is vital for travel demand estimation and urban resources planning. Among various existing ridership modeling methods, direct demand model with ordinary least square (OLS) multiple regression as a representative has considerable advantages over the traditional four-step model. Nevertheless, OLS multiple regression neglects spatial instability and spatial heterogeneity from the magnitude of the coefficients across the urban area. This paper aims to focus on modeling and analyzing the factors influencing metro ridership at the station level.

This paper constructs two novel direct demand models based on geographically weighted regression (GWR) for modeling influencing factors on metro ridership from a local perspective. One is GWR with globally implemented LASSO for feature selection, and the other one is geographically weighted LASSO (GWL) model, which is GWR with locally implemented LASSO for feature selection.

The results of real-world case study of Shenzhen Metro show that the two local models presented perform better than the traditional global model (OLS) in terms of estimation error of ridership and goodness-of-fit. Additionally, the GWL model results in a better fit than GWR with global LASSO model, indicating that the locally implemented LASSO is more effective for the accurate estimation of Shenzhen metro ridership than global LASSO does. Moreover, the information provided by both two local models regarding the spatial varied elasticities demonstrates the strong spatial interpretability of models and potentials in transport planning.

The main contributions are threefold: the approach is based on spatial models considering spatial autocorrelation of variables, which outperform the traditional global regression model – OLS – in terms of model fitting and spatial explanatory power. GWR with global feature selection using LASSO and GWL is compared through a real-world case study on Shenzhen Metro, that is, the difference between global feature selection and local feature selection is discussed. Network structures as a type of factors are quantified with the measurements in the field of complex network.