Sam Thomas

Loyalty intentions: Does the effect of commitment, credibility and awareness vary across consumers with low and high involvement?

Purpose – This article aims to present a model linking loyalty intention, brand commitment, brand credibility and brand awareness. The model shows the mediating role of brand commitment and brand credibility on loyalty intention. The researchers also investigated the changes in the given model under high and low involvement conditions, explicitly considering involvement as between-subject differences rather than between-product differences. The change in customer loyalty intention under varying levels of product involvement is a highly debated topic among researchers. Design/methodology/approach – The model was tested on a sample of 318 executives who have bought and are using deodorants. The respondents had given responses for loyalty intentions, brand commitment, brand credibility, brand awareness and involvement towards the brand of deodorant that they use. Confirmatory factor analysis was used to validate the tool for measurement of constructs and multi-group structural equation modelling for testing the hypotheses and comparing the nested models. Findings – The difference between high and low involvement groups in the given model supports the hierarchy-of-effects view. We found that attitude precedes behaviour for highly involved individuals but followed a different hierarchy among the individuals with low involvement. Research limitations/implications – This research investigates the proposed model for a single product category and so the scope of generalisability is limited to the product selected. This research has considered behavioural intention rather than the behaviour in this study. Practical implications – The study demonstrates the differences in the hierarchy-of-effects among low/high involvement groups. Thus, the findings will have an impact on the approach of practitioners, as different strategies will have to be adopted for the enhancement of loyalty intentions based on the difference in perceived involvement of consumers. Originality/value – This paper shows the need to differently target consumers with different levels of perceived involvement, within the same product class and thus between-subject involvement can be used as a segmentation variable.

Software Development Project Risk: A Second Order Factor Model Validated in the Indian Context

Software development risk points to an aspect of a development task, process or environment which, if ignored, tends to adversely affect the project performance. Observations from literature show that while many studies on software project risk construct have been done in developed countries, there is scarcity of literature from Asian countries, especially India. Hence, this research was formulated with an objective of studying software development project risk in the Indian context. Data related to the presence of risk items was collected from 527 software development projects in India. This data was factor analyzed to identify five major risk dimensions namely Team risk, Project planning and Execution Risk, External risk, User risk and Project complexity risk. The resulting factor structure was validated through Confirmatory Factor Analysis. Software project risk was seen to be best represented by a second order factor model with five first order factors.

How does software project risk vary across projects? An exploratory study from India

Software development risk continues to be a major concern for software development organisations across the globe. Review of literature shows that while many studies on risk construct have been done, there is a scarcity of empirical studies on the possible variation in risk across project and organisational characteristics. This research, based on the data collected from 527 software development projects in India, checks how risk levels vary across different types of projects executed with different types of organisations. Major risk dimensions were identified and confirmed through a combination of exploratory factor analysis and confirmatory factor analysis. Possible variation in the risk scores across the sample was checked through a series of one way ANOVA tests. Risk levels were seen to be highly influenced by select project characteristics and organisational attributes.

Direct and indirect effect of brand experience on true brand loyalty: role of involvement

The purpose of this paper is to investigate the role of product and customer dimensions in the contribution of brand experience to the formation of true brand loyalty. The dimensions included are brand credibility, affective commitment and involvement. Synthesising past studies, the researcher proposes brand credibility and affective commitment to mediate the relationship between brand experience and true brand loyalty. Furthermore, the researcher investigates the variation in hierarchical pattern, i.e. brand experience-brand credibility affective commitment-true brand loyalty, under different levels of involvement.,The variations in hierarchy were compared by design. The authors investigated the variations in hierarchy on the basis of products which belong to different level of involvement, on the basis of individual differences in involvement, and on the basis of the interaction of product involvement and subject involvement. Multi-group invariance tests in SEM were used to explore model variations.,The hierarchy-of-effect model was found to vary based on the level of product involvement, subject involvement and interaction involvement. Three patterns of hierarchy have been observed: the first pattern was observed in high-high groups (both product involvement and subject involvement were high), the second pattern was observed in low-low groups (both product and subject involvements were low) and the third pattern among high-low or low-high groups.,The variation observed highlights the need to segment the market by interaction involvement. This would be useful for managers engaged in building sustainable consumer-brand relationships.,This study considered the interaction of product approach and subject approach in defining involvement which is rarely attempted in research. The study also integrates the variations in the role of customer dimensions, namely involvement, brand credibility and affective commitment with the relationship between the central constructs brand experience and true brand loyalty. The variations observed are among a socio-economically homogeneous sample of respondents.

A Discriminant Model for Classifying Software Project Performance

Project managers are concerned about completing the projects on time and cost. IT projects across the globe are notorious for their time and cost overruns. This paper presents output from a comprehensive study on software development risk and project outcome with respect to the projects executed by software companies in India. Based on the data collected from over 300 projects, the authors developed a discriminant model for predicting the project outcome category based on risk scores of a project. The discriminant models developed are seen to possess adequate prediction accuracy to be used in practice. The models can help the project managers in early detection of likely project failures and hence to initiate appropriate counter strategies.

Discriminating entrepreneurship intentions: empirical study of young Indian IT professionals

The Indian IT industry has contributed significantly to its economic growth in the last two decades. Understanding the drivers of entrepreneurship intention (EI) among young professionals can help advance the entrepreneurial activity in the industry, and frame regulatory/academic policies. 184 new-to-the-corporate IT professionals and 30 real entrepreneurs, all aged in their 20s and mostly in early 20s, were studied to understand their EI and its drivers. Applying theory of planned behaviour, attitude towards entrepreneurship (ATE), subjective norms (SNs) and perceived behavioural control (PBC) were considered as the antecedents of EI. The sample was classified into three categories: non-entrepreneurs with low EI, non-entrepreneurs with high EI, and real entrepreneurs. Discriminant analysis was done to validate this classification and the relationship between EI and its three antecedents. ATE was the strongest predictor of entrepreneurial behaviour. The study extends the existing literature on EI by providing the Indian IT industry context and by adding real entrepreneurs in scope.

Indian IT Industry Firms: Moving towards an Active Innovation Strategy

This paper aims to describe the changing innovation strategies of Indian IT industry firms. Indian firms are responding to global technological discontinuities proactively and faster, compared to the past. Innovations continue to be process driven, however, there is significant focus on non-linear, products & platforms-led growth strategies. There has been an upward shift in R&D/IP emphasis, as empirical data suggests, and emphasis on collaborative innovation. Firms are willing to make riskier investments compared to past. The paper also discusses some of the challenges the players face, as they build the next generation innovations and offerings. Nature of emerging technologies provides further scope for firms to come up with innovative products, services and solutions. Key conclusion is that the innovation strategy of Indian IT industry has changed from ‘reactive’ to ‘active’.

An Integrative Model Linking Risk, Risk Management and Project Performance: Support from Indian Software Projects

Software development organizations across the globe are concerned about the high rate of project failures. Two constructs which are hypothesized to have significant impact on project outcome are risk and risk management. Risk points to an aspect of a development task, process or environment which, if ignored, tends to adversely affect the project performance. Risk management is defined as the mechanism for identifying, addressing and eliminating software risk items before they become threats to project success. Based on the data collected from 527 software development projects in India, this research develops an integrated model linking these three constructs. Structural Equation Modeling was used to develop and validate the models. The models show how the impact of risk management on project outcome may be mediated by risk.