Diffusion of Kyoto's clean development mechanism

To date, developed countries can only tap mitigation opportunities in developing countries by investing in projects under the Clean Development Mechanism (CDM). Yet CDM investments have so far failed to reach all of the high-potential sectors identified in IPCC reports. This raises doubts about whether the CDM will be able to generate an adequate supply of credits from the limited areas where it has proved successful. Our paper examines the current trajectory of potential mitigation entering the CDM pipeline and projects it forward under the assumption that the diffusion of the CDM will follow a path similar to other kinds of innovations. Projections are then compared to pre-CDM predictions of the mechanism's potential market size used to assess Kyoto's cost, in order to discern whether limits on the types of project entering the pipeline will also limit the eventual supply of certified emission reductions (CERs). The main finding of the paper is that the mechanism is on track to deliver an average annual flow of roughly 700 million CERs by the close of 2012 and nearly to 1100 million tons by 2020. Parameter tests suggest that currently identified CDM investments will exceed early model predictions of the potential market for CDM projects.     

Globalisation and the Major Accounting Firms

Driven mainly by deregulation and technological change, globalisation is a common tendency among firms seeking better opportunities and lower costs. This paper discusses the nature of globalisation in accounting firms, in particular the "Big 5" (the paper was written before the Big 5 became the Big 4). The firms seem to exhibit two forms of the phenomenon: establishment globalisation (spread of a firm's establishments in different locations) and product globalisation (addition of new services in a bid to extend global reach). The paper examines the effect of globalisation on the demand for accounting information and how globalisation transforms the major accounting firms.     

SYSTEMATIC RISK IN A PURELY RANDOM MARKET MODEL: SOME EMPIRICAL EVIDENCE FOR INDIVIDUAL PUBLIC UTILITIES

A minimum norm quadratic (MINQU-) type of OLS estimator is derived. The estimator is used to test if the betas of the single factor market (SFM) model are random for a sample of utilities for two contiguous periods. The estimated betas for individual utilities vary considerably over time. The statistical significance of such nonstationarity depends on both the utilities and period studied. The relative reduction in the mean square error (MSE) from using a GLS (and not OLS) estimator of beta, when beta is purely random, can be substantial for some utilities but is modest on average.     

Inclusive apparel shopping experiences for older consumers in China: product attributes and retail environment

ABSTRACT

The study explored apparel shopping experiences of older Chinese consumers, which integrate apparel product and retail environment aspects from an inclusive strategy perspective. Research questions include: What factors contribute to older Chinese consumers’ satisfaction and dissatisfaction? What are the major implications of older consumers’ (dis)satisfying shopping experience? What role can fashion practitioners play to make the retail environment and apparel products more accessible to the aging segment? Critical Incident techniques were used for data collection at a community park in Beijing. A total of 151 usable critical incidents from 84 older Chinese informants (55 years and older) were included in the data analysis. Content analysis with deductive qualitative data analysis method was used. Findings suggest that the older Chinese consumers assess their shopping experiences largely based on shopping outcome achieved (product purchased). This is in contrast to the movement toward more experiential focus in the developed markets in the recent decades. A significant number of tangible product attributes (including design/styling, comfortability/fit, and material) and intangible attributes (such as price and product assortment) contributed to the older Chinese informants’ satisfying or dissatisfying shopping experience. Aspects related to retail environment, including retail atmospherics and service quality were also important, but to a lesser extent than product attributes. This study represents an early attempt to explore how the tangible and intangible aspects of product attributes and retail environment contribute to the aging Chinese consumer’s shopping experience. Findings of the Chinese older consumers’ utilitarian, rather than experiential focus in their shopping experience evaluation provide insights on this market segment and valuable implications are developed.     

Cigarette and Alcohol Expenditures in Malaysia: Implications for Anti‐Smoking and Drinking Policies*

A number of studies have examined alcohol and cigarette consumption, but none have explored demand for both products simultaneously even though consumption decisions are likely often related. The present study uses microdata from the 2009/2010 Malaysian Household Expenditure Survey. A novel bivariate Tobit model that accounts for error heteroscedasticity is used to estimate Malaysian consumers' decisions to purchase cigarettes and alcohol and amount spent for each. The results indicate that household income and regional location, and the age, gender, education level and occupation type of the household head are associated with consumption decisions and expenditure levels, with some variation by ethnic group, suggesting the importance of these characteristics in policy deliberations to reduce consumption.     

The establishment of industrial branding through dyadic logistics partnership success (LPS): The case of the Malaysian automotive and logistics industry

Logistics partnerships across dyadic and triadic relationship networks have been the basis of extensive research in the extant literature. It is well understood that competitive advantage within logistics and distribution and within supply chains are driven by value-adding aspects of not only the core competencies of each tier in the network, but also via tangential supporting factors. It is also well understood that there is a strong relationship between logistics and distribution and marketing functions, particularly in product-based organisations. In addition to deepening our understanding of how successful partnerships throughout the source–make–deliver continuum can be optimised, this research also seeks to identify how a supporting element in terms of industrial branding and marketing can lead to relational sustainability. Hence, this paper outlines the relationship between logistics partnership success (LPS) factors and the inherent link to industrial branding establishment and business sustainability within the Malaysian automotive industry (specifically, car manufacturers). Adopting a multiple case study approach, findings suggest that there is a strong association between logistics service performance (LSP) provided by the third party logistics provider (TPLP) and the development and support of a mutual brand image for both the TPLP and the car manufacturer. We contribute to the extant literature on logistics partnership and industrial branding through linking LSP with the creation and maintenance of an industrial branding strategy for both parties in the context of the Malaysian automotive industry.     

Eco‐efficiency of high‐yielding variety rice cultivation after accounting for on‐farm environmental damage as an undesirable output: an empirical analysis from Bangladesh

This study computes the eco‐efficiency of high‐yielding variety (HYV) rice production by including an on‐farm environmental damage index (OFEDI) as an undesirable output using data envelopment analysis. It then identifies its determinants by applying an interval regression procedure on a sample of 317 farmers from north‐western Bangladesh. Results reveal that the mean level of the OFEDI‐adjusted production efficiency (i.e. eco‐efficiency) is 89 per cent, whereas ignoring OFEDI adjustment (i.e. with OFEDI = 0) reduces the mean level of efficiency to 69 per cent, implying that the production of undesirable output or on‐farm environmental damage induces an efficiency loss of 20 per cent with significant differences across regions. The proportion of farmers’ income from HYV rice agriculture, land ownership, extension services and socio‐environmental living standard are the significant determinants of improving eco‐efficiency. Policy implications include investments in extension services and land reform measures to increase land ownership, which will synergistically improve eco‐efficiency of HYV rice production in Bangladesh.     

R&D and regional competitiveness: a study of global entrepreneurial firms

We quantify, using data from the World Bank’s Enterprise Surveys and the World Economic Forum’s Global Competitiveness Index, the empirical relationship between global competitiveness and R&D investment activity as well as the independent relationship between global competitiveness and R&D investments across geographic regions of economic development. We also explore alternative measures of the effectiveness of R&D investments. Our findings suggest that R&D investments are a possible policy target variable in high-income regions for policy makers to consider for increasing firms’ global competitiveness.

     

Predicting accounting fraud using imbalanced ensemble learning classifiers – evidence from China

The current research aims to launch effective accounting fraud detection models using imbalanced ensemble learning algorithms for China A-Share listed firms. Based on a sample of 33,544 Chinese firm-year instances from 1998 to 2017, this research respectively established one logistic regression and four ensemble learning classifiers (AdaBoost, XGBoost, CUSBoost, and RUSBoost) by 12 financial ratios and 28 raw financial data. Additionally, we divided the sample into the train and test observations to evaluate the classifiers' out-of-sample performance. In detail, we applied two metrics, namely, Area under the ROC (receiver operating characteristic) curve (AUC) and Area under the Precision-Recall curve (AUPR), to evaluate classifiers' discriminability. In the supplement test, this study put forward an algebraic fused model on the basis of the four ensemble learning classifiers and introduced the sliding window technique. The empirical results showed that the ensemble learning classifiers can detect accounting fraud for the imbalanced China A-listed firms far more effectively than the logistic regression model. Moreover, imbalanced ensemble learning classifiers (CUSBoost and RUSBoost) effectively performed better than the common ensemble learning models (AdaBoost and XGBoost) in average. The algebraic fused model in the supplement test also obtained the highest average AUC and AUPR among all the employed algorithms. Our results offer firm support for the potential role of Machine Learning (ML)-based Artificial Intelligence (AI) approaches in reliably predicting accounting fraud with high accuracy. Similarly, for the Chinese settings, our ML-based AI offers utmost advantage in forecasting accounting fraud. Finally, this paper fills the research gap on the applications of imbalanced ensemble learning in accounting fraud detection for Chinese listed firms.