Complementarity,status similarity and social capital as drivers of alliance formation

Using data on U.S. investment banking firms’ syndication in underwriting corporate stock offerings during the 1980s, this study explores the factors that drive alliance formation between two specific firms. We compare resource complementarity, status similarity, and social capital as a basis of alliance formation. The findings indicate that the likelihood of investment banks’ alliance formation is positively related to the complementarity of their capabilities, as well as their status similarity. Social capital arising from banks’ direct and indirect collaborative experiences also plays a very important role in alliance formation. The number of deals given by a lead bank to a potential partner over the past three years has an inverted U‐shaped relationship to the probability that the lead bank will invite the potential partner to form an alliance. Our findings indicate that status similarity and social capital have a stronger effect on alliance formation in initial public offering deals than in secondary offering deals, as the former are more uncertain than the latter. Using these findings, we discuss the role of complementarity, status similarity, and social capital in alliance formation. Copyright © 2000 John Wiley & Sons, Ltd.     

Use of neurometrics to choose optimal advertisement method for omnichannel business

ABSTRACT

The omnichannel business has deeply affected retail practices and promotional strategies. This paper presents an empirical evaluation of omnichannel advertisement channels using neurometric response of the viewers. High precision camera and Galvanic Skin Response sensors were used to record neurometric information of respondents. The response of forty volunteers against a set of cosmetic advertisements was recorded to train a computer for predicting expected neurometric response for an advertisement channel. The recorded neurometric data was further analyzed to develop a set of business rules to measure the effectiveness of any advertisement channel. Later, comparative analysis of various advertisement channels was done.     

Do socially motivated self‐help groups perform better? Exploring determinants of micro‐credit groups’ performance in Eastern India

Group‐based micro‐credit initiatives, as part of the broader social and solidarity‐based finance initiatives, have gained prominence over the past decade, especially in developing economies like India. Lending to the poor, especially women, through micro‐credit groups, are significantly associated with the utilization of commons. Apart from their financial operations, self‐help groups promote social empowerment activities and collective action following a dual bottom‐line approach. However, the causal role of the group's motivation towards pursuing social objectives has not been explored in the past. The present study, therefore, investigates the interlinkages between the group's intrinsic motivation and efficiency using an innovative two‐stage double bootstrapped DEA‐based methodology. Results from the study affirm that apart from traditional factors like maturity, accessibility and group management, the motivation of the group is a crucial determinant of social efficiency. Additionally, the group's loan‐to‐savings ratio and receipt of cash payments significantly affect its long‐term financial sustainability. Micro‐credit groups cannot contribute sustainably as a viable alternative to traditional means of access to credit if it merely offers innovative forms of financing and consumption. They need to be socially aligned to serve the community better and contribute to the group's overall performance and galvanize community‐based resource management.     

Searching for religious discrimination among childcare workers

We implement a lab‐in‐the‐field experiment among childcare workers in Chandigarh, India, to evaluate discriminatory attitudes of the Hindu workers toward Muslim children. We use a third‐party allocation game that controls for selfish payoff‐maximizing preferences across the treatments and focus exclusively on distributional attitudes. Our results indicate that the workers in our sample are primarily motivated by welfare‐based criteria in making their allocation decisions and do not practice discrimination based on religious identities.     

Mapping supply dynamics in renewable feedstock enabled industries: A systems theory perspective on ‘green’ pharmaceuticals

This paper provides a multi-stage multi-layer mapping methodology for capturing the macro-level supply chain dynamics that govern industrial systems using renewable feedstocks. The mapping approach combines the Industrial Systems Mapping and System Dynamics principles to systematically capture the interrelations across: (i) institutional players, (ii) sector specialists, (iii) products and intermediates, (iv) production operations, and (v) firms within the supply chain. The interfaces are further explored at four interconnected and mutually interacting theme areas of analysis, namely: (i) renewable chemical feedstocks, (ii) production technologies, (iii) target markets, and (iv) value and economic viability. We demonstrate the applicability of our approach by mapping the dynamics in industrial systems for the production of ‘green’ pharmaceuticals, particularly via the illustrative case of paracetamol. Through the use of the proposed integrated mapping process the case study demonstrates the principal interrelationships and inter-firm dynamics between the different layers of analysis. Three main drivers are identified that could enhance supply network transformations for improved viability of these developing industrial systems, namely: (i) regulatory conformance with market requirements, (ii) system level feasibility assessment of given renewable feedstocks, and (iii) target market volume demand. The causal feedback elements of the provided mapping technique indicate that it could support the analysis of industrial systems’ transformation dynamics enabled by renewable feedstocks. The standardisation of the methodology and its elements provides for an effective visualisation technique with cross-industry relevance.     

Fighting Software Piracy: Some Global Conditional Policy Instruments

This study examines the efficiency of tools for fighting software piracy in the conditional distributions of software piracy. Our paper examines software piracy in 99 countries over the period 1994–2010, using contemporary and non-contemporary quantile regressions. The intuition for modelling distributions contingent on existing levels of software piracy is that the effectiveness of tools against piracy may consistently decrease or increase simultaneously with the increasing levels of software piracy. Hence, blanket policies against software piracy are unlikely to succeed unless they are contingent on initial levels of software piracy and tailored differently across countries with low, medium and high levels of software piracy. Our findings indicate that GDP per capita, research and development expenditure, main intellectual property laws, multilateral treaties, bilateral treaties, World Intellectual Property Organisation treaties, money supply and respect for the rule of law have negative effects on software piracy. Equitably distributed wealth reduces software piracy, and the tendency not to indulge in software piracy because of equitably distributed wealth increases with the increasing software piracy levels. Hence, the negative degree of responsiveness of software piracy to changes in income levels is an increasing function of software piracy. Moreover, the relationships between policy instruments and software piracy display various patterns: U-shape, Kuznets-shape, S-shape and negative thresholds. A negative threshold represents negative estimates with the increasing negative magnitude throughout the conditional distributions of software piracy. We also discuss the policy implications of our study.     

Testing the Tracking Efficiency of Commodity Exchange Traded Funds (ETFs) across the Bearish and Bullish Market Regimes: Evidence from Indian Gold ETFs

Commodity exchange traded funds (ETFs) help investors gain exposure to the underlying commodity in digital form. The present article attempts to examine the performance characteristics of 12 gold ETFs in India across the bear and bull markets. ETFs’ sensitivity to their underlying asset (gold prices) is observed to be lower during the bearish market regime, and, as such, the tracking error is found to be higher during the bearish market regime. Further, volume is reported to bear a significant positive impact on the tracking ability of ETFs whereas volatility and pricing deviation are found to negatively impact the tracking ability of ETFs.     

Revisiting the Purpose of Selling: Toward a Model of Responsible Selling

Selling as a profession and sales management as an organizational function have undergone major changes that were driven by the evolutionary journey of the marketing discipline. The extant value cocreation paradigm is recrafting the purpose of selling. This paper explores the conceptual development of a selling paradigm that is more responsible to its customers. Specifically, in Business-to-Business (B2B) context, the cost of any selling behavior that compromises customer interest could be of disastrous proportions. Building on the theoretical foundations of self-regulation and job demands-resources theory, this paper develops a conceptual model of responsible selling by integrating self-leadership literature with the emerging paradigm of value-based selling. The conceptual model outlines several research propositions for empirical validation and discusses its potential implications for sales managers and sales organizations.     

Ad-Hoc Black–Scholes vis-à-vis TSRV-based Black–Scholes: Evidence from Indian Options Market

This research paper examines one-day-ahead out-of-sample performance of the volatility smirk-based options pricing models, namely, Ad-Hoc-Black–Scholes (AHBS) models on the CNX Nifty index options of India. Further, we compare the performance of these models with that of a TSRV-based Black–Scholes (BS) model. For the purpose, the study uses tick-by-tick data. The results on the AHBS models are highly satisfactory and robust across all the subgroups considered in the study. Notably, a daily constant implied volatility based ad-hoc approach outperforms the TSRV-based BS model substantially. The performance of the ad-hoc approaches improves further when the smile/smirk effect is considered. For the estimation of the implied volatility smile, we apply three weighting schemes based on the Vega and liquidity of the options. All the schemes offer equally competing results. The major contribution of the study to the existing literature on options pricing is in terms of the ex-ante examination of the ad-hoc approaches to price the options by calibrating volatility smile/smirk on a daily basis.

     

Do Vendor Cues Influence Purchase Intention of Online Shoppers? An Empirical Study Using S-O-R Framework

The purpose of the current research is to understand the influence of vendor cues like brand reputation. Brand familiarity and offline presence on trust and attitude of online shoppers and consequently on online purchase intention. Data was collected through a web based survey. The findings of the study reported that vendor offline cues have a strong and positive impact on the online purchase intentions of the shoppers. Further, this study also contributed by proving that the trust has a strong relationship with purchase intention as compare to attitude.