Search results

The purpose of this paper is twofold: first, to investigate the direct effect of internal and external drivers on full implementation of the green supply-chain management (GSCM) practice; and second, to investigate the direct effect of internal drivers and indirect effect of external drivers on the full implementation of the GSCM practice.

The study is based on the data collected from 30 to 35 furniture small and medium enterprises (SMEs) chosen from each surveyed region. In this case, the selected SMEs should have been conducted some GSCM practices. So, the total number of samples used in this study is 100 SMEs. The relationships between internal and external drivers and the success of the implementation of the GSCM practices are analyzed using structural equation modeling.

The results of this study have revealed that internal and external drivers, which consist of involvement, technology, financial, regulation and customer pressure, have a direct effect on early adoption of GSCM practices. Among these drivers, technology gives the most significant effect. The results have also shown that only financial factor has a direct effect on the full implementation of GCSCM practices, whereas regulation and customer pressure have positive effect on the full implementation through early adoption of GSCM practices.

Among the limitations of this study is related to the sample that was restricted to SMEs of furniture in three regions. The other limitation could be related to variable involved as internal and external drivers. This study has only used involvement, technology, knowledge, financial, and regulation and customer pressure as the antecedent variables of early adoption of the GSCM practices. Moreover, this study has only used the Likert scale as an approach to measure the implementation of GSCM practice management, which could be the source of bias in expressing the level of the implementation.

From the internal side of enterprises, the top management or the owner of SMEs can develop an effective comprehensive environmental strategy. This strategy requires the top management of SMEs show an environment oriented, allocate a specific person for implementing the GSCM practice and learn about the current technology that can support the environmentally friendly products, and also allocate the specific budget to support the implementation of GSCM practice. Moreover, since the study also found that financial factor was just the only factor having a direct effect on the full implementation of GSCM practices; therefore, the government should help the SMEs of furniture in developing low cost-GSCM implementation techniques and also provide easiness for the SMEs to get the needed fund for implementing the GSCM practice.

The research has confirmed that regulation and customer pressure have the positive and significant effect on the full implementation of GSCM practices. It may encourage the government to make some policy related to improvement of the implementation of GSCM practice by SMEs of wooden furniture, specifically in the Central Java Province. Another implication would be to encourage the customer to make purchasing oriented decision for the implementation of GSCM practices by the SMEs of wooden furniture.

This study contributes to the literature of GSCM by combining the critical factors of implementation of GSCM practices toward internal and external drivers and empirically testing the direct and indirect impacts on the level of adoption of GSCM practices.

This study aims to create a system dynamics simulation model to forecast the performance of small and medium-sized enterprises (SMEs) if some decision-making is executed to reduce the negative of the coronavirus disease 2019 (COVID-19) pandemic. In particular, this study will focus on SMEs that belong to the furniture industry because the furniture industry is one of the leading industries in Indonesia.

The study develops a system dynamics-based model by using three subsystems, i.e. the “production subsystem,” “demand and revenue subsystem” and “raw material (or wood supply) subsystem.”

The best scenario is the third scenario which increases the capacity to the normal situation and government subsidy during and after the pandemic. This scenario gives the best performance for industry revenue and gross domestic product (GDP). However, for the government, the most significant expenditure occurs in the third scenario. This seems a trade-off for the government whether to save the wooden-based furniture industry by encouraging the industry to continue operating during the pandemic accompanied by high subsidies or limiting the activities of the wooden-based furniture industry to prevent the spread of COVID-19 by providing low subsidies.

First, this study does not try to combine the system dynamics (SD) methodology with the other method or use a multi-methodology since SD has several limitations and the other method may have several advantages compared to SD. Second, the models used in this study do not consider the decline in forest area and quality. Third, the demand for wooden-based furniture is obtained from historical data on domestic and foreign sales and fourth, the model does not include the government budget as a constraint to make any subsidy to help the SMEs.

This study provides essential insights into implementing the policies in the world pandemic situation when SMEs face lockdown policy.

The study revealed that relevant policy scenarios could be built after simulating and analyzing each scenario's effect on SMEs' performance during the pandemic.

This study will enrich the previous study on the impact of the pandemic on SMEs and the dynamic system modeling on SMEs. The previous study discussed the pandemic's impact on SME performance and the impact's analysis in isolation from the dynamic nature of SME owners' decisions or government policy. In this study, the impact generated from the pandemic situation could be different depending on the decision and policies taken by managers from SMEs and the government.

The purpose of this paper is examining how financial inclusion can be enhanced in rural and remote areas in emerging economies through the adoption of Financial technologies. The study examines the direct influence of technological characteristics, facilitating conditions, trust and perceived risk on adoption of FinTech. Furthermore, the study examines the mediating effects of facilitating conditions and moderating effects of education level in adoption of FinTech.

The study employed quantitative research design. Stratified and simple random sampling were employed to identify areas in which respondents will be collected. Drop and Pick method was further employed to collect 275 valid and reliable responses. Structural equation modeling was used to analyze the data and assess the reliability and validity of the measurement model. Structural model analysis was employed to examine the hypothesized relationship.

The results show that compatibility, complexity agent trust, perceived risk and facilitating have significant influence on adoption of FinTech. Furthermore, the findings show that facilitating conditions mediate the relationship between all technological characteristics and FinTech adoption except the relationship between compatibility and FinTech. The study also has found that education level moderates the relationship between observability and FinTech adoption as well as trialability and FinTech adoption.

This study employed cross-sectional research-based techniques in collecting data for analyzing the hypothesized relationship. However, the drawback of cross-sectional may impact the findings of this study over a long time. Therefore, future studies must consider conducting longitudinal studies which may collect data over some time for analysis of the FinTech adoption. Furthermore, the generalization of these findings should be considered carefully by other countries which are not economically similar to Tanzania and developed countries. This also provides room for future studies to examine the same area in countries with different economic development.

This study contributes to knowledge into two folds: First there is limited knowledge on adoption of FinTech in emerging economies; the study addresses the knowledge gap by providing empirical findings which will help scholar. Furthermore, less studies have examined the moderating effects of facilitating condition in adoption of technology. This study addresses the knowledge gap by examining the moderating influence of moderating influence of facilitating conditions. Also, this study provides empirical findings which will help policymakers to implement strategy that will speed-up financial inclusion in rural and isolated areas in emerging economies.