Developing design principles for the digitalisation of purchasing and supply management

This paper develops an approach to evaluating designs for digitalisation interventions in purchasing and supply management (PSM), and identifies some fundamental design principles for such interventions. A set of advanced technologies for digitalisation and a theory-based set of seven value drivers for PSM are identified for the proposed grid to facilitate the design of applications and interventions for digitalising PSM. The grid relates the digital technologies to the PSM value drivers in a matrix-like manner, allowing the structured consideration of the space defined by these two dimensions. The proposed approach to the strategic evolution of digitalisation in PSM is tested and its utility is demonstrated in analyses of practitioner literature and multiple case-study-based perspectives on PSM digitalisation. Two fundamental design principles relating to the use of the grid, or to the filling of its space, are set out, thus the research provides new theoretical perspectives on the design of advanced forms of PSM digitalisation. The proposed grid may be used in application design, communicating current and future states of PSM digitalisation to stakeholders, and specifically in developing a future-oriented strategy with a digitalization element for the PSM function.     

Asymmetric information consolidation and price discovery: Inferring bad news from insider sales

Due to the paucity of sources of negative firm‐specific information, US capital markets have more difficulty identifying and incorporating bad news into stock prices than they do good news. Even though insider selling is a potentially important proxy for undisclosed bad news, researchers have difficulty ex ante identifying information‐based sales due to an inability to separate liquidity‐motivated from information‐based insider trades. We hypothesize that when insiders in multiple firms sell shares of one firm in which they are insiders and at the same time buy shares of other insider portfolio firms, the sale is more likely to be information‐based, since the proceeds are reinvested. Conversely, when an insider sells one firm without purchasing others or sells multiple insider firms the sale is likely liquidity‐motivated. We find that insider sales identified as information‐based using this algorithm are followed by significant negative abnormal returns. Information‐based sales are also more likely to be associated with delistings, earnings declines and earnings restatements. Analysts are also more likely to revise their earnings forecasts downwards for these firms. It is thus possible to ex ante identify insider sales with information content. Our results will be of interest to investors and also to regulators designing insider trading rules.     

Collaboration risk management in IT-enabled asymmetric partnerships: Evidence from telestroke networks

Information technology (IT)-enabled partnerships can unlock previously unattainable value propositions between organizations that have resource, capability, and other asymmetries by allowing larger organizations access to niche and local resources while providing smaller organizations access to enhanced resources and capabilities. However, recent studies have shown that many IT-enabled asymmetric partnerships often fail because the organizations do not effectively manage the involved collaboration risks. Most organizations focus on the strategic aspect of whether partners behave cooperatively or competitively, while paying scant attention to the operational aspect of bringing together partner contributions through coordination. To examine this problem, we report on a case study of two hub-spoke networks that used telemedicine to facilitate expertise sharing and decision making about stroke treatment at emergency departments in rural hospitals (spokes) based on information exchanges with remote neurologists at academic medical centers (hubs). As a result, we contribute to the inter-organizational information systems literature by explaining how organizations in IT-enabled asymmetric partnerships manage collaboration risks. We demonstrate how partners in such relationships perceive and approach strategic cooperation and operational coordination risks differently. We also explain how collaboration interactions change over time as the partners manage risks based on needs and resource endowments. Drawing on these findings, we provide guidance to organizations on how to manage sustainable IT-enabled asymmetric partnerships in general, and telestroke networks in particular.     

Motivators and barriers to sustainable food consumption: Qualitative inquiry about organic food consumers in a developing nation

The present research attempts to qualitatively explore the motivators and barriers of organic food consumption in the Indian context. The data were collected using semistructured in‐depth interviews and analyzed using grounded theory. The theoretical sampling technique was used to interview 34 consumers who have purchased organic food in the past. The findings reported health consciousness, environmental consciousness, social identity, consumer ethnocentrism, and concern for farmers as the factors that motivate organic food purchase among consumers. The factors such as high prices of organic food, unavailability, trust issues, and limited marketing communications from the firms were identified as major barriers to organic food purchase and consumption. The study is one of the initial attempts to qualitatively explore the consumers' motivation for organic food consumption in the Indian context. The findings will help policymakers to devise suitable strategies so that they can effectively target the organic food choices by understanding the motivators/barriers, and promote the sustainable lifestyle in the society, as food consumption plays a crucial role in achieving environmental sustainability.     

Machine Learning and Expert Judgement: Analyzing Emerging Topics in Accounting and Finance Research in the Asia–Pacific

In this paper, we focus on the question to what extent machine learning (ML) tools can be used to support systematic literature reviews. We apply a ML approach for topic detection to analyze emerging topics in the literature—our context is accounting and finance research in the Asia–Pacific region. To evaluate the robustness of the approach, we compare findings from the automated ML approach with the results from a manual analysis of the literature. The automated approach uses a keyword algorithm detection mechanism whereby the manual analysis uses common techniques for qualitative data analysis, that is, triangulation between researchers (expert judgement). From our paper, we conclude that both methods have strengths and weaknesses. The automated analysis works well for large corpora of text and provides a very standardized and non-biased way of analyzing the literature. However, the human researcher is potentially better equipped to evaluate current issues and future trends in the literature. Overall, the best results might be achieved when a variety of tools are used together.     

LIQUIDITY AND ASSET PRICING UNDER THE THREE‐MOMENT CAPM PARADIGM

We examine whether the use of the three‐moment capital asset pricing model can account for liquidity risk. We also make a comparative analysis of a four‐factor model based on Fama–French and Pástor–Stambaugh factors versus a model based solely on stock characteristics. Our findings suggest that neither of the models captures the liquidity premium nor do stock characteristics serve as proxies for liquidity. We also find that sensitivities of stock return to fluctuations in market liquidity do not subsume the effect of characteristic liquidity. Furthermore, our empirical findings are robust to differences in market microstructure or trading protocols between NYSE/AMEX and NASDAQ.     

Equal Opportunities for Men and Women in the EU: A Commentary

This commentary examines the main objectives of the European Commission Fourth Medium-Term Action Programme on Equal Opportunities for Men and Women (1996–2000). An assessment is made of the objectives, and the methods proposed to achieve them.     

Green marketing,public policy and managerial strategies

Green marketing subsumes greening products as well as greening firms. In addition to manipulating the 4Ps (product, price, place and promotion) of the traditional marketing mix, it requires a careful understanding of public policy processes. This paper focuses primarily on promoting products by employing claims about their environmental attributes or about firms that manufacture and/or sell them. Secondarily, it focuses on product and pricing issues. Drawing on multiple literatures, it examines issues such as what needs to be greened (products, systems or processes), why consumers purchase/do not purchase green products and how firms should think about information disclosure strategies on environmental claims. Copyright © 2002 John Wiley & Sons, Ltd and ERP Environment.     

Efficient Liability Rules: Complete Characterization

Received May, 18, 2000; revised version received March, 19, 2001     

On the generalization of Rao,Hartley and Cochran's scheme

Summary The problem considered in this paper is a generalization of the usual Rao, Hartley and Cochran (RHC) scheme. In the usual RHC scheme the population ofN units is randomly divided inton groups wheren is the size of the sample. In this paper we propose to divide the population under consideration into (n+k) random groups wherek is some positive integer. Then a sample ofn groups is selected by using simple random sampling without replacement (SRSWOR). The expressions for the unbiased estimator of population total, its variance and the unbiased estimate of variance have been obtained under the proposed sheme. The condition under which the proposed sheme is more efficient than the usual RHC scheme has also been investigated.