Identifying stakeholders’ perspectives on the success factors of halal tourism in the city of Makassar: a group model building approach

Purpose Islamic attributes and activities need to be developed in compliance with the halal concept to attract potential Muslim tourists and ensure the success of halal tourism. Although the literature shows that many factors can influence the success of halal tourism, a complete picture of the success factors of halal tourism in a city is still very limited. As such, this explorative study aims to examine stakeholders’ perspectives regarding the antecedents of halal tourism success and the benefits of halal tourism for the city. Design/methodology/approach Qualitative system dynamics modeling was used for this study, and Makassar (a successful halal tourism city) was considered as the basis for the study. A causal loop diagram (CLD) of halal tourism was developed using the group model building technique to elicit stakeholders’ knowledge and assumptions. Network analysis and feedback loop analysis were used to identify the driving factors of successful halal tourism. Findings Two factors need to be taken into account by halal tourism stakeholders in the city: support from the central and local government and improving and maintaining potential tourists’ perceptions of the city. There are four benefits of halal tourism success for the city: an increase in the number of micro-, small- and medium-sized halal businesses in the city, increased support from the central and local government to further develop halal tourism infrastructure in the city, increased word-of-mouth promotion of Makassar as a tourism destination and a decrease in the price of halal tourism components (e.g. food and accommodation). Originality/value The resulting CLD shows the interlinkage between political, societal and economical factors that could influence the success of halal tourism development. In particular, the findings show how governments and tourism stakeholders need to promote halal tourism socialization in the community and improve the public perception of this type of tourism. Therefore, the findings can help destination stakeholders and tourism developers in other cities develop halal tourism potential.

USING SYSTEM DYNAMICS MODELING TO ASSESS THE IMPACT OF CONNECTICUT GOOD SAMARITAN LAWS: A PROTOCOL PAPER

Background We applied a participatory system dynamics (SD) modeling approach to evaluate the effectiveness and impact of Connecticut Good Samaritan Laws (GSLs) that are designed to promote bystander intervention during an opioid overdose event and reduce opioid overdose-related adverse outcomes. Our SD model can be used to predict whether additional revisions of the statutes might make GSLs more effective. SD modeling is a novel approach for assessing the impact of GSLs; and, in this protocol paper, we describe its applicability to our policy question, as well as expected outcomes of this approach. Methods This project began in February 2021 and is expected to conclude by March 2022. During this time, a total of six group model-building (GMB) sessions will have been held with key stakeholders to elicit feedback that will, in turn, contribute to the development of a more robust SD model. Session participants include bystanders who witness an overdose, law enforcement personnel, first responders, pharmacists, physicians, and other health care professionals who work in at least two major metropolitan areas of Connecticut (New Haven and Hartford). Due to the restrictions imposed by the COVID-19 pandemic, the sessions are being held virtually via Zoom. The information obtained during these sessions will be integrated with a draft SD model that has already been developed by the modeling team as part of a previous CDC-funded project. Model calibration and policy simulations will then be performed to assess the impact of the current GSLs and to make recommendations for future public policy changes. Discussion An SD modeling approach enables capture of complex interrelationships among multiple health outcomes to better assess the drivers of the opioid epidemic in Connecticut. The model simulation results are expected not only to align with current real-world data but also to recreate historical trends and infer future trends in a situationally relevant fashion. This will facilitate the work of policy makers who are devising and implementing time-sensitive changes to address opioid overdose-related deaths at the state level. Replicating our approach as described can be applied to make similar improvements in other jurisdictions. CONTRIBUTIONS TO THE LITERATURE - System dynamics (SD) modeling and group model-building (GMB) approaches enable the group to start with a simple concept model and apply the collective knowledge of the group to finish the session with a much more developed model that can produce impressively accurate simulation results. - The model will be used to understand the impact of Connecticut Good Samaritan Laws (GSLs), as well as their limitations, and to deduce factors to further improve public health laws to counter opioid overdose-related deaths. - The approach can be applied to other jurisdictions, taking into account local conditions and existing Good Samaritan legislation. KEYWORDS: System dynamics modeling, group model building, opioid overdose deaths, opioid use disorder, Good Samaritan laws

Exploring construction workers' attitudinal ambivalence: a system dynamics approach

PurposeThis study aimed to identify driving factors of safety attitudinal ambivalence (AA) and explore their influence. Construction workers' intention to act safely can be instable under conflicting information from safety management, co-workers and habitual unsafe behaviour. Existing research explained the mechanism of unsafe behaviours as individual decisions but failed to include AA, as the co-existence of both positive and negative attitude.Design/methodology/approachThis study applied system dynamics to explore factors of construction workers' AA and simulate the process of mitigating the ambivalence for less safety behaviour. Specifically, the group model building approach with eight experts was used to map the causal loop diagram and field questionnaire of 209 construction workers were used to collect empirical data for initiating parameters.FindingsThe group model building identified five direct factors of AA, namely the organisational safety support, important others' safety attitude, emotional arousal, safety production experience and work pressure, with seven feedback paths. The questionnaire survey obtained the initial values of the factors in the SD model, with the average ambivalence at 0.389. The ambivalence between cognitive and affective safety attitude was the highest. Model simulation results indicated that safety experience and work pressure had the most significant effects, and safety experience and positive attitude of co-workers could compensate the pressure from tight schedule and budget.Originality/valueThis study provided a new perspective of the dynamic safety attitude under the co-existence of positive and negative attitude, identified its driving factors and their influencing paths. The group model building approach and field questionnaire surveys were used to provide convincible suggestions for empirical safety management with least and most effective approaches and possible interventions to prevent unsafe behaviour with tight schedule and budget.

Investigating the Socio-Economic and Livelihoods Impacts of African Swine Fever in Timor-Leste: An Application of Spatial Group Model Building

Small-scale pig farming is highly important to the economic and social status of households in Timor-Leste. The presence of an African Swine Fever (ASF) outbreak in Timor-Leste was confirmed in 2019, a major concern given that around 70% of agricultural households practice pig farming. This research used a virtual spatial group model building process to construct a concept model to better understand the main feedback loops that determine the socio-economic and livelihood impacts of the ASF outbreak. After discussing the interaction of reinforcing and balancing feedback loops in the concept model, potential leverage points for intervention are suggested that could reduce the impacts of ASF within socio-economic spheres. These include building trust between small-scale farmers and veterinary technicians, strengthening government veterinary services, and the provision of credit conditional on biosecurity investments to help restock the industry. This conceptual model serves as a starting point for further research and the future development of a quantitative system dynamics (SD) model which would allow ex-ante scenario-testing of various policy and technical mitigation strategies of ASF outbreaks in Timor-Leste and beyond. Lessons learned from the blended offline/online approach to training and workshop facilitation are also explored in the paper.

EXPLORING SYSTEMIC FORCES THAT INFLUENCE SUSTAINABLE DESIGN TRANSITIONS

In this research some systemic forces to sustainable design are described and mapped out, along with key areas, dimensions and stakeholders. These results are visualized in a causal loop diagram (CLD), which was the outcome of a group model building approach supported by a literature review. Within the proposed system model, represented by the system-level variables and their relationships within the CLD, some potential leverage points that can help make product design better contribute to sustainability are identified and described. These can be found in the balancing and reinforcing feedback loops of the CLD as well as the mapping to societal dimensions of sustainability transitions and stakeholder groups. Among the stakeholder groups, business managers, scientific researchers and engineering designers can be tied to the design community. Future research is proposed to build on these initial results to deepen the knowledge about the systemic drivers and barriers and leverage the contribution of design practice to sustainable development.

Developing A Group Model Building Causal Loop Diagram to Understand Millennial Generation Trust in Twitter as Early Warning System for Natural Disaster

Nowadays, Twitter is used as an Early Warning System (EWS) for disasters because of the speed and many users. Based on Asosiasi Penyedia Jasa Internet Indonesia (APJII) data, in 2017, almost 50% of internet users in Indonesia are born in 1983-1998. They are called the millennial generation. Therefore, this study aims to explore the trust of millennials towards Twitter as an EWS. This study utilizes the conceptual model from System Dynamics named Causal Loop Diagram (CLD) to identify the factors and the causal relationship among millennials' factors to trust Twitter as an EWS. It involves ten participants from the millennial generation, consisting of five passive Twitter users and five active Twitter users. A semi-structured interview was conducted with all participants to build the initial CLD gathered from each participant's perspective. Afterward, the initial CLD was verified by all participants through Focus Group Discussion. A group model building CLD that represents the influencing factors and their causal relationship of millennial generation trust in Twitter as EWS for a natural disaster is successfully developed from this study. The tweet frequency, the number of followers, the account credibility, the verified account, the level of trust in social media, and the content quality are considered the underlying factors of active and passive users to trust in Twitter as an EWS natural disaster.