Exploring geographical dispersion in Thailand-based food supply chain (FSC)

Purpose: The purpose of this paper is to explore the key influential factors and their implications on food supply chain (FSC) location decisions from a Thailand-based manufacturer's view. Design/methodology/approach: In total, 21 case studies were conducted with eight Thailand-based food manufacturers. In each case, key influential factors were observed along with their implications on upstream and downstream FSC location decisions. Data were collected through semi-structured interviews and documentations. Data reduction and data display in tables were used to help data analysis of the case studies. Findings: This exploratory research found that, in the food industry, FSC geographical dispersion pattern could be determined by four factors: perishability, value density, economic-political forces, and technological forces. Technological forces were found as an enabler for FSC geographical dispersion whereas the other three factors could be both barriers and enablers. The implications of these four influential factors drive FSC towards four key patterns of FSC geographical dispersion: local supply chain (SC), supply-proximity SC, market-proximity SC, and international SC. Additionally, the strategy of the firm was found to also be an influential factor in determining FSC geographical dispersion. Research limitations/implications: Despite conducting 21 cases, the findings in this research are based on a relatively small sample, given the large size of the industry. More case evidence from a broader range of food product market and supply items, particularly ones that have significantly different patterns of FSC geographical dispersions would have been insightful. The consideration of additional influential factors such as labour movement between developing countries, currency fluctuations and labour costs, would also enrich the framework as well as improve the quality and validity of the research findings. The different strategies employed by the case companies and their implications on FSC location decisions should also be further investigated along with cases outside Thailand, to provide a more comprehensive view of FSC geographical location decisions. Practical implications: This paper provides insights how FSC is geographically located in both supply-side and demand-side from a manufacturing firm's view. The findings can also provide SC managers and researchers a better understanding of their FSCs. Originality/value: This research bridges the existing gap in the literature, explaining the geographical dispersion of SC particularly in the food industry where the characteristics are very specific, by exploring the internationalization ability of Thailand-based FSC and generalizing the key influential factors - perishability (lead time), value density, economic-political forces, market opportunities, and technological advancements. Four key patterns of FSC internationalization emerged from the case studies. © Emerald Group Publishing Limited.

Simulating early adoption of alternative fuel vehicles for sustainability

We quantify the conditions that might trigger wide spread adoption of alternative fuel vehicles (AFVs) to support energy policy. Empirical review shows that early adopters are heterogeneous motivated by financial benefits, environmental appeal, new technology, and vehicle reliability. A probabilistic Monte Carlo simulation model is used to assess consumer heterogeneity for early and mass market adopters. For early adopters full battery electric vehicles (BEVs) are competitive but unable to surpass diesels or hybrids due to purchase price premium and lack of charging availability. For mass adoption, simulations indicate that if the purchase price premium of a BEV closes to within 20% of an in-class internal combustion engine (ICE) vehicle, combined with a 60% increase in refuelling availability relative to the incumbent system, BEVs become competitive. But this depends on a mass market that values the fuel economy and CO2 reduction benefits associated with BEVs. We also find that the largest influence on early adoption is financial benefit rather than pro-environmental behaviour suggesting that AFVs should be marketed by appealing to economic benefits combined with pro-environmental behaviour to motivate adoption. Monte Carlo simulations combined with scenarios can give insight into diffusion dynamics for other energy demand-side technologies. © 2012 Elsevier Inc.

Building performance simulation for the management of thermal performance risks in buildings subject to climate change

This paper reports on research that uses building performance simulation and uncertainty analysis to assess the risks that projected climate change poses to the thermal performance of buildings, and to their critical functions. The work takes meteorological climate change predictions as a starting point, but also takes into account developments and uncertainties in technology, occupancy, intervention and renovation, and others. Four cases are studied in depth to explore the prospects of the quantification of said climate change risks. The research concludes that quantification of the risks posed by climate change is possible, but only with many restrictive assumptions on the input side.

Investigating the link between well-being and energy use; an explorative case study between passive and active domestic energy management systems

The aim of this study was to explore how the remote control of appliances/lights (active energy management system) affected household well-being, compared to in-home displays (passive energy management system). A six-week exploratory study was conducted with 14 participants divided into the following three groups: active; passive; and no equipment. The effect on well-being was measured through thematic analysis of two semi-structured interviews for each participant, administered at the start and end of the study. The well-being themes were based on existing measures of Satisfaction and Affect. The energy demand for each participant was also measured for two weeks without intervention, and then compared after four weeks with either the passive or active energy management systems. These measurements were used to complement the well-being analysis. Overall, the measure of Affect increased in the passive group but Satisfaction decreased; however, all three measures on average decreased in the active group. The measured energy demand also highlighted a disconnect between well-being and domestic energy consumption. The results point to a need for further investigation in this field; otherwise, there is a risk that nationally implemented energy management solutions may negatively affect our happiness and well-being. © 2013 Elsevier Ltd.