LOW-INCOME HOUSING IN INDIAN CITIES: SOME CONSIDERATIONS FOR POLICY

Across cities in India, migrant groups, squatters and the urban poor residing in slums have played a crucial role in developing low-income housing. This form of housing is closely connected to the economic activity of the poor, which in turn contributes to the wider urban economy. It also enables the poor to consolidate their position in the city and make claims on the city administration for infrastructure. However, such housing has been bracketed as 'informal' and lacks legitimacy. Policies concerning low-income housing must address this issue while enabling the poor to further their economic and entrepreneurial initiatives.     

Optimal pricing and ordering policy for deteriorating inventory under trade credit in demand declining market

In market, the retailer tries to sell the product at much higher price than the purchase cost. In this study, an attempt is made to develop optimal ordering and pricing policy for a retailer when the supplier offers a credit period to settle the account. The demand of a product is declining with time and units in the retailer＇s inventory are subject to constant deterioration. An algorithm is developed to determine the optimal selling price and the ordering quantity to maximize the retailer＇s profit. The numerical examples are given to support the development of the mathematical model. The sensitivity analysis of critical parameters is carried out to observe the changes in the decision variables and objective function.     

Experimenting with Supply Chain Learning (SCL): Supplier Diversity and Ethnic Minority Businesses

This paper reports on an innovative UK-based ‘Supply Chain Learning’ (SCL) initiative to encourage the corporate sector to consider supplier diversity in respect of ethnic minority businesses. This follows academic and policy interest in programmes to empower ethnic minority enterprises to achieve breakout to mainstream markets and business growth. The first phase of the initiative, entitled Supplier Development East Midlands (SDEM) is examined. By adopting an inter-organisational action learning approach, some of the key attributes of the programme are delineated, focusing on the recurrent action-reflection cycle taking place in a learning group comprising SDEM, LPOs (Large Purchasing Organisations) and small EMSs (Ethnic Minority Suppliers).     

Till death do us part…but not always: Six antecedents to a customer's relational preference in buyer-seller exchanges

Since its emergence in the early 1990s as marketing's newest paradigm or school of thought, research in the area of relationship marketing has been proliferating. From the customer's perspective, initial attempts to become lifelong partners with key sellers or suppliers were appealing. However, as these propositions multiply in number and carry with them increasing burdens in terms of time and commitment, customers are reticent to enter into long-lasting relationships with all sellers. In this paper, we consider relationship formation from the customers' perspective and examine the antecedents to a customer's preference for a relational exchange orientation versus a transactional exchange orientation. Our belief is that, depending upon a set of contextual factors surrounding the exchange, customers will opt for a relational orientation with suppliers in some cases and for a more transactional orientation in others.     

Linking routines to operations capabilities: A new perspective

A typical approach to studying capabilities in the operations management literature is to assess the intended or realized competitive operational performance and their contribution to business and organizational objectives. While it is crucial to identify the operational performance that helps create competitive advantage, it is equally important to understand the means for delivering the needed performance at the operational level. Drawing on the resource-based view (RBV), we argue that routines are a critical source of operations capabilities and subsequently investigate operations capabilities by means of their underlying routines. Because a common problem to studying capabilities is the ambiguous and confusing definitions, we conduct an extensive literature review to address the semantic confusion among various definitions of capabilities and delineate it from other related terms. We identify improvement and innovation as two critical plant level capabilities, each consisting of a bundle of interrelated yet distinct routines. We then empirically measure the two capabilities as second-order latent variables and estimate their effects on a set of operational performance measures. The results suggest that routines form internally consistent bundles which are significantly related to operational performance. This supports our notion of “capabilities as routine bundles” that are difficult to imitate and thus a source of competitive advantage.     

Model selection in univariate time series forecasting using discriminant analysis

When a large number of time series are to be forecast on a regular basis, as in large scale inventory management or production control, the appropriate choice of a forecast model is important as it has the potential for large cost savings through improved accuracy. A possible solution to this problem is to select one best forecast model for all the series in the dataset. Alternatively one may develop a rule that will select the best model for each series. Fildes (1989) calls the former an aggregate selection rule and the latter an individual selection rule. In this paper we develop an individual selection rule using discriminant analysis and compare its performance to aggregate selection for the quarterly series of the M-Competition data. A number of forecast accuracy measures are used for the evaluation and confidence intervals for them are constructed using bootstrapping. The results indicate that the individual selection rule based on discriminant scores is more accurate, and sometimes significantly so, than any aggregate selection method.     

Building Better Theory by Bridging the Quantitative–Qualitative Divide*

abstract Qualitative methods for data collection and analysis are not mystical, but they are powerful, particularly when used to build new or refine existing theories. This article provides an introduction to qualitative methods and an overview of tactics for ensuring rigor in qualitative research useful for the novice researcher, as well as more experienced researchers interested in expanding their methodological repertoire or seeking guidance on how to evaluate qualitative research. We focus our discussion on the qualitative analytical technique of grounded theory building, and suggest that organizational research has much to gain by coupling of use of qualitative and quantitative research methods.     

Comparison of test vs. control treatments using distance optimality criterion

We consider the problem of comparison of one test treatment (τ₀) with a set of v control treatments (τ₁, τ₂, …, τ_v) using distance optimality [DS-optimality] criterion introduced by Sinha (1970) in some treatment-connected design settings. It turns out that the nature of DS-optimal designs is quite similar to that for the usual A−, D− and E− optimality criteria. However, the optimality problem is quite complicated in most situations. First we deal with the CRD model and derive DS-optimal allocations for a given set of treatments. The results are almost identical to the A-optimal allocations for such problems. Then we consider a block design set-up and examine the nature of DS-optimal designs. In the process, we introduce the method of weighted coverage probability and maximize the resulting expression to obtain an optimal design. Received: December 1999