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Co-branding is popular with partnerships between well-known and new brands. In a laboratory study, this paper aims to examine the effects of a single ally and multiple allies on quality perception of a brand. The results suggest that the quality perception of the new brand depends on the co-branding strategy.

For dual-brand alliances, a single-factor design was used, with secondary brand quality level (high, medium and low) as the independent variable. Three advertisements were created by manipulating quality levels of the single partner. For multiple-brand alliances, a 2 × 3 between-subjects factorial design was used in the experiment. The two factors were diversification (homogeneous vs heterogeneous) and quality levels of the alliance (high-end, mixed and low-end).

The results suggest that the number of brand partners significantly affected the perceived quality of the primary brand. For both dual- and multi-brand alliances, the quality level of the secondary brand positively influenced the perceived quality of the primary brand. For multiple-brand alliances, even though the highest quality perceptions of the primary brand are in the heterogeneous conditions, the heterogeneity of partners (partners across different product categories) did not affect the quality perception of the primary brand.

One limitation of the current study is that it only addresses one type of brand alliance: co-promotion. The generalization of these findings to other forms of brand alliances (e.g. ingredient branding: Intel with IBM, Dell and HP) merits further investigation. Also, in this study, respondents processed the information in a relatively low-involvement condition (note that the target ad was presented along with filler ads). They were more likely to use brand names as heuristic cues to form their judgments. Because an alliance partner also assumes risks, future research should consider the effect of the alliances on the secondary brand.

Understanding brand alliances (especially multiple-brand alliances) is critical for new product managers and marketers. Introducing a new brand has higher risk and failure rates. Companies may lower these risks by co-branding with established brands. However, they should carefully consider the diversification and quality level of the partners. If brand managers position their product as “high quality (luxury)” or “low quality (budget)”, they should choose high- (or low-) quality partners from different product categories (heterogeneous high-end or low-end alliances) because diversification strengthens the primary brand. For a single-partner alliance, the secondary brand should be of high quality.

This paper extends the brand alliance literature beyond single-partner to multiple-partner alliances. With multiple partners, one can explore several critical aspects of an alliance, e.g. quality variance and product class diversity across the partners.

Modern interactionism asserts that both the P (person) and the E (environment or situation) should be considered simultaneously in predicting attitudes and behaviors. In this paper, we apply the interactionist view to salesforce research. Specifically, we use salesforce socialization as an example to illustrate how interactionist concepts from psychology can be effectively applied in salesforce research. The role of qualitative research in this context is explored.

The main objective of this study is to identify the determinants of TV ads avoiding behavior between light and heavy avoiders in greater Cairo. To achieve the study objective, five hypotheses have been developed and tested by such statistical techniques as discriminant analysis, t‐tests, MannWhitney tests, and Chi Square tests. A questionnaire has been designed to collect data from a systematic random sample of adults in social clubs and shopping centers in greater Cairo. The number of usable questionnaires in data analysis was 364. The study findings show that all respondents except 3 were doing one or more of TV ads avoiding behavior. Cognitive avoiding represents the most frequently used avoiding behavior by light and heavy TV ads avoiders. The results also demonstrate that perceptions, attitudes toward advertising, and some motives were determinants of TV ads avoiding behavior. On the other hand, it was found that all demographic and socioeconomic characteristics, except types of channels, were not determinants of TV ads avoiding behavior between light and heavy TV ads avoiders. The study concludes with a number of academic and practical recommendations.

This paper not only aims to validate the environment Kuznets curve concerning five Asian economies but also attempts to analyze the impact of some additional factors like financial development, energy consumption and foreign direct investment (FDI) on carbon emissions.

This paper applies pooled mean group approach on the variables of a panel of five Asian economies namely India, Pakistan, Bangladesh, Sri Lanka and Malaysia for a period of 35 years from 1980 to 2014.

This study finds that while moderate economic growth as well as moderate financial development increase carbon emissions, accelerated or exponential economic growth as well as exponential financial development eventually reduce the level of carbon emissions. Energy consumption was found to have a direct and significant relationship with carbon emissions. FDI inflows when analyzed on a stand-alone basis were observed to have an inverse relationship with carbon emissions, while FDI inflows when clubbed with financial development were observed to have a direct relationship with carbon emissions.

The findings of this study, which validate the environmental Kuznets curve, suggest striving for higher economic growth, even if it causes increased carbon emissions to begin with, as the effects on carbon emissions would eventually get reversed when the economic growth accelerates at a higher rate. This study also suggests the appropriate routing of FDI through a mature and developed financial sector to leverage its impact on the environment in a positive way.

To the best of the knowledge of the authors of this paper, there has not been any research carried out so far, which has analyzed the impact of the combination of variables selected for this study concerning the five Asian economies covered in this paper.

In initial public offerings (IPOs), the media plays a pivotal role by disseminating the information to the investors who generally lack the expertise to understand the information through the prospectus. Thus, media coverage can impact the investment decision of the investors and the IPO performance. Media typically covers the IPO before listing, suggesting that it may play an important role in explaining the opening price rather than the closing price on the day of listing. Therefore, this study aims to disaggregate the traditional IPO underpricing into three categories: voluntary, pre-market and post-market and provides a comparative analysis of the media sentiments impact on the traditional and disaggregated IPO underpricing. The authors’ disaggregated IPO underpricing analysis will facilitate the investors in making an effective investment strategy based on media sentiments.

The study deploys sentiment analysis using bags of n (2) grams approach to gauge the sentiments on 2,891 media articles and uses “robust-regression” technique to analyze them on a sample of 222 Indian IPOs during 2009–2018.

The study reports that the sentiment score is positively related to the traditional underpricing; the sentiment score is positively associated with the pre-market underpricing and does not have any significant relationship with the post-market underpricing; the number of media articles does not play a significant role in explaining the IPO underpricing. The findings highlight the presence of a semi-strong form of efficiency in the Indian IPO market.

Existing literature focuses that the role of media on IPO performance is based on the developed countries. IPO laws differ based on the countries. For instance, in India, investors can check the demand by the other categories of investors on a real-time basis. Thus, it is interesting to study whether, with such a high level of transparency, media can explain IPO performance in the Indian market. Media generally covers IPO before listing; therefore, the present study disaggregates the IPO underpricing to evaluate the role of media on the primary and secondary market separately. It will help the investors to decide when to enter and exit the market.

The aim of this paper is to identify the criteria that are used for vendor or supplier rating, prioritize these criteria based on the industry inputs and develop a vendor rating model. The data were collected from an Indian start-up working in product development using three-dimensional printing (3DP).

Factors of importance for vendor rating were identified through industry visits, and interacting with the industry experts from the start-up under consideration, substantiated by extensive review of relevant literature. A questionnaire-based survey was carried out to further narrow down the factors important to the industry, prioritizing them with a pairwise comparison analysis as envisaged in the analytical hierarchy process (AHP) technique along with the calculation of consistency ratios. Technique for order preference by similarity to ideal solution (TOPSIS) methodology was further used for data aggregation.

This research brought forward the criteria that are useful for rating vendors or suppliers with reference to 3DP sector.

This paper integrates AHP and TOPSIS to solve a multi-criteria vendor rating problem. The attempt was made to make vendor rating process universal so that it can encompass all the vendors of the firm.

The purpose of this study is to examine the differential impact of qualitative and quantitative informational signals within the merger and acquisition (M&A) press releases on deal completion and duration. A significant percentage of deals by emerging market acquirers get abandoned before completion, and those that are completed have a longer duration. The limited information about the operations of acquirers from emerging markets creates suspicion among the stakeholders involved in deal resolution, hindering the completion of deals. Thus, using the signal-feedback paradigm, authors investigate how informational signals in the M&A press release impact the deal resolution.

The study employs content analysis on M&A press releases announced by firms from five emerging economies: Brazil, Russia, India, China and South Africa. The technique is applied based on the exploration-exploitation framework developed by March (1991) to categorize the announced deal motives (qualitative information). Next, the authors identify the percentage of relevant quantitative information disclosed in the press release, following which results are obtained using logistic and ordinary least square regressions.

The study reports that deals with declared exploratory motives take longer to complete. Additionally, deals disclosing higher percentage of quantitative disclosure exhibit lower completion rate and increased deal duration.

This is the first study to provide evidence that familiarity bias impacts deal duration as relative to exploitation deals that are familiar to the stakeholders; exploratory deals take longer to conclude. Further, our analysis indicates that a greater percentage of quantitative disclosure may not always reduce information risk but rather be interpreted negatively in the form of the acquirer’s overconfidence in the deal’s potential.

The current work explores the relationship between workplace ostracism, emotional intelligence (EI) and organizational change cynicism. This paper also aims to examine how dimensions of EI moderate the relationship between workplace ostracism and organizational change cynicism.

This study intends to examine the contribution of independent variable as well as moderating variable towards the outcome. Therefore, Pearson product–moment correlation and moderated regression analyses have been carried out to verify the hypotheses. To validate the tools upon the employees of India, authors have carried out measurement model analyses through AMOS and checked their composite reliability, convergent validity (average variance extraction [AVE]) and discriminant validity (square root of AVE). This study followed a simple random sampling technique with 276 employees (Male: N = 150, Mage = 34.34, female: N = 126, Mage = 31.57) from three manufacturing units of Odisha, an Eastern part of India.

Results showed that workplace ostracism was positively related to organizational change cynicism. However, only two dimensions of EI, namely, appraisal and regulation of self-emotion (ARSE) and other’s emotional appraisal were negatively related to organizational change cynicism. Moderated regression analysis indicates that positive relationship between workplace ostracism and organizational change cynicism is stronger for employees with low ARSE and other emotional appraisals than those with higher scores.

The researchers conclude this paper with inputs for developing a suitable training module on EI, specifically focusing on various emotional management skills.

To the best of the authors’ knowledge, this study is first of its kind on workplace ostracism and organizational change cynicism among Indian employees in the manufacturing sector. This study also examines the moderating role of EI on workplace ostracism and organizational change cynicism, which has been somehow inadequate in the present epoch.

This study initially aims to identify the barriers to the big data analytics (BDA) initiative and further evaluates the barriers for knowing their interrelations and priority in improving the performance of manufacturing firms.

A total of 15 barriers to BDA adoption were identified through literature review and expert opinions. Data were collected from three types of industries: automotive, machine tools and electronics manufacturers in India. The grey-decision-making trial and evaluation laboratory (DEMATEL) method was employed to explore the cause–effect relationship amongst barriers. Further, the barrier's influences were outranked and cross-validated through analytic network process (ANP).

The results showed that “lack of data storage facility”, “lack of IT infrastructure”, “lack of organisational strategy” and “uncertain about benefits and long terms usage” were most common barriers to adopt BDA practices in all three industries.

The findings of the study can assist service providers, industrial managers and government organisations in understanding the barriers and subsequently evaluating interrelationships and ranks of barriers in the successful adoption of BDA in a manufacturing organisation context.

The paper is one of the initial efforts in evaluating the barriers to BDA in improving the performance of manufacturing firms in India.

This paper aims to present an improvement to the power quality of the grid by using a colliding body optimization (CBO) based proportional-integral (PI) compensated design for a grid-connected solar photovoltaic-fed brushless DC motor (BLDC)-driven water pumping system with a bidirectional power flow control. The system with bidirectional power flow allows driving the pump at full proportions uninterruptedly irrespective of the weather conditions and feeding a grid when water pumping is not required.

Here, power quality issue is taken care of by the optimal generation of the duty cycle of the voltage source converter. The duty cycle is optimally generated by optimal selection of the gains of the current controller (i.e. PI), with the CBO technique resulting in a nearly unity power factor as well as lower total harmonic distortion (THD) of input current. In the CBO technique, the gains of the PI controller are considered as agents and collide with each other to obtain the best value. The system is simulated using MATLAB/Simulink and validated in real time with OPAL RT simulator, OP5700.

It was found that the power quality of grid using the CBO technique has improved much better than the particle swarm optimization and Zeigler–Nichols approach. The bidirectional flow of control of VSC allowed for optimum resource utilization and full capacity of water pumping whatever may be weather conditions.

Improved power quality of grid by optimally generation of the duty cycle for the proposed system. A unit vector tamplate generation technique is used for bidirectional power transfer.