The use of the consumer ethnocentrism and consumer animosity scales in Iran: A research note

This research note presents the results of testing the reliability of two constructs from the country‐of‐origin literature—consumer ethnocentrism and consumer animosity—within the Iranian national consumer environment. Consumer ethnocentrism, developed by Shimp and Sharma (1987), measures the level of consumer ethnocentrism and has been used broadly in several countries. The consumer animosity scale (Klein, Ettenson, & Morris, 1998), a newer construct, has not been widely tested for its reliability in diverse national contexts. The country of Iran, with its ongoing dispute and hostility with the United States, provides an ideal context to test both of these constructs. We utilized the original animosity scale and an adapted version of the ethnocentrism scale. Both scales performed well and provide strong support for the reliability of each construct, allowing other researchers a high degree of confidence in their application. This finding suggests that these research tools may be useful and can be expanded to the greater Middle East region. © 2009 Wiley Periodicals, Inc.     

Trend forecasting for stability in supply chains

This paper revisits the use of trend forecasting to determine ordering policy in supply chains by viewing it as a part of the control process for making the supply responsive to demand. Trend forecasting is often used to assess demand — a tracked variable in the control context, which drives supply — a tracking variable. Used in this way, it is often observed to increase instability creating the so-called bullwhip effect. Trend is used on the other hand with reliability to increase stability in controller control, but with the difference that a trend of a tracking variable is used to drive correction. While both processes involve use of trend to determine policies for achieving reliable performance, the outcomes of the former are variable while those of the later can create improvement in control with certainty. The similarities and differences between the two processes are discussed and guidelines developed for applying trend forecasting to enhance stability in supply chains.     

Clusters,Chains and Compliance: Corporate Social Responsibility and Governance in Football Manufacturing in South Asia

A recent concern in the debate on corporate social responsibility (CSR) in developing countries relates to the tension between demands for CSR compliance found in many global value chains (GVCs) and the search for locally appropriate responses to these pressures. In this context, an emerging and relatively understudied area of interest relates to small firm industrial clusters. Local clusters offer the potential for local joint action, and thus a basis for improving local compliance on CSR through collective monitoring and local governance. This article explores the interrelationship between global governance, exercised through GVC ties, and local governance, via cluster institutions, in ensuring compliance with CSR pressures. It undertakes a comparative analysis of two leading export-oriented football manufacturing clusters in South Asia that have both faced common challenges on child labour. The article shows that both forms vertical and horizontal governance have played a part in shaping the response of the two clusters on child labour. Moreover, these two distinct forms of governance have also led to quite differentiated outcomes in terms of forms of work organization and child labour monitoring. This raises broader questions on how global CSR demands can locally be better embedded and the conditions under which football stitchers labour in these new work forms.     

Analysing customers' reviews and ratings for online food deliveries: A text mining approach

The purpose of this study was to explore the relationship between online reviews and ratings through text mining and empirical techniques. An Indian food delivery portal ( Zomato.com ) was used, where 50 restaurants on Presence Across Nation (PAN) basis were selected through stratified random sampling. A total of 2530 reviews were collected, scrutinized, and analysed. Using the NVivo software for qualitative analysis, seven themes were identified from collected reviews, out of which, the ‘delivery’ theme was explored further for identifying sub-themes. Linear regression modelling was used to identify the variables affecting delivery ratings and sentiment analysis was also performed on the identified sub-themes. Regression results revealed that hygiene and pricing (delivery subthemes) demonstrated lower delivery ratings. These variables can be established as indicators for restaurants and related online food delivery services to build their business model around them. Similarly, negative sentiments were observed in pricing and hygiene sub-themes. Restaurants and online food services can enhance hygiene levels of their food delivery process in order to receive higher delivery ratings. Similarly, pricing of food items can be modified such that customers are not deterred from ordering the items—food and ordering service do not become cost-prohibitive. This study devised a standardized methodology for analysing vast amounts of online user-generated content (UGC). Findings from this study can be extrapolated to other sectors and service industries such as, tourism, cleaning, transportation, hospitals and engineering especially during the pandemic.     

Mining resettlement and rural development in Malaysia

The Malaysian government has employed 3 kinds of resettlement schemes: 1) resettlement of farmers under modern agricultural and land development programs to grow cash crops; 2) resettlement of rural population in well-guarded locations to isolate them from communist insurgents; and 3) resettlement and compensation of population displaced thorough resource exploitation such as construction of dams and mining. The Kinta Valley resettlement is examined in the example of 3 villages where tin mining encroached on their agricultural land. 98 households were included in the sample from Batu Bertudung, Tekka, and Jelutung that had been settled in the 1940s. The villagers were eventually evacuated and sustained technological, pecuniary, and psychological losses. The economic loses involved property, land, and crops, and social losses comprised social networks, neighborhood, and stability. 81.7% of the villagers who were left landless successfully insisted on complete relocation of their villagers in new villages in claims to the respective tin mining companies through their newly formed village action committees in the mid-1960s. The compensation consisted of 1) group compensation by planned resettlement, 2) cash payment, and 3) replacement of the former plot with another piece of land. Social needs were not included in the calculation and the compensation received reflected roughly their economic worth at the time. The villagers of Tekka and Jelutung had their houses rebuilt which were comparable to their old homes using new materials and stronger foundations. Those from Batu Bertudung were resettled in another village, and were compensated in cash to rebuild their homes themselves. Basic amenities were insufficient: new wells had to be dug, the public standpipe was overused, and only dirt roads were constructed. The government provided most basic amenities 5-6 years later under the rural development program.     

On solving bias‐corrected non‐linear estimation equations with an application to the dynamic linear model

In a seminal paper, Mak, Journal of the Royal Statistical Society B, 55, 1993, 945, derived an efficient algorithm for solving non‐linear unbiased estimation equations. In this paper, we show that when Mak's algorithm is applied to biased estimation equations, it results in the estimates that would come from solving a bias‐corrected estimation equation, making it a consistent estimator if regularity conditions hold. In addition, the properties that Mak established for his algorithm also apply in the case of biased estimation equations but for estimates from the bias‐corrected equations. The marginal likelihood estimator is obtained when the approach is applied to both maximum likelihood and least squares estimation of the covariance matrix parameters in the general linear regression model. The new approach results in two new estimators when applied to the profile and marginal likelihood functions for estimating the lagged dependent variable coefficient in the dynamic linear regression model. Monte Carlo simulation results show the new approach leads to a better estimator when applied to the standard profile likelihood. It is therefore recommended for situations in which standard estimators are known to be biased.     

The influence of product-placement type & exposure time on product-placement recognition

This study examines the extent to which product-placement type and exposure time explain the rate at which viewers recognise brand names affiliated with product placements in films. The results support the industry practice of classifying product placements into creative and on-set, since placement type has a significant impact on viewer recognition, even when the measure of viewer recognition is adjusted for the effects of false recognition. The effect of exposure time attained by product placement on viewer recognition is moderated by product-placement type. The theoretical and practical implications of these results are discussed.     

On the Aggregate Impact of Exchange Rate Variability on EU Trade

The paper assesses the aggregate impact of exchange rate variability on EU trade. A small econometric model is constructed and estimated for five countries: France, Italy, Germany, the UK and Belgium. The results show that there exists a long-term relationship between trade variables and relative costs, demand, exchange rates and expected exchange rates. No such relation exists with respect to volatility. It is also found that while the most important determinants of trade variables are relative wages and demand, variability is also responsible for a decrease in the growth rate of these variables.