Search results

The purpose of this paper is to develop a typology of heuristics in business relationships. We distinguish between four categories: (1) general heuristics used in the context of a business relationship but that may also (and are often) used in other contexts; (2) relational context heuristics that are typically used in a relational context; (3) relational information heuristics that rely on relational information and (4) genuine relational heuristics that use relational information and are applied in relational contexts.

We draw on existing literature on heuristics and business relationships to inform our conceptual paper.

We apply this typology and discuss specific heuristics that fall under the different categories of our typology. These include word-of-mouth, tit-for-tat, imitation, friendliness, recognition and trust.

We contribute to the heuristics literature by providing a novel typology of heuristics in business relationships. Emphasizing the interdependence between heuristics and business relationships, we identify genuine relational heuristics that capture the bidirectional relationships between business relationships and heuristics. Second, we contribute to the business relationships literature by providing a conceptual framework for understanding the types of heuristics managers use in business relationships and by discussing examples of specific heuristics and how they are applied in relational contexts.

We contribute to practice by providing a simple framework for making sense out of the “universe” of heuristics for business relationships.

Our paper provides a novel typology for understanding heuristics in business relationships.

This study combines different perspectives on herding, viewing it as a social network heuristic in comparison to other heuristics. The purpose is to use the heuristic view of herding as found in early literature and test it on grounds of efficiency and payoff, in essence, combining the heuristic and rational agent view of herding. The simulated double auction setting includes agents embedded in a social network, allowing for an examination of herding alongside rational behaviour and imperfect signals.

In each round of the simulation, levels of homophily, density and fractions of types of agents is set and agents are allowed to follow their respective heuristics under those conditions. Characteristics of the social network, such as the size, levels of different homophilies, density and fractions of different types of agents are varied randomly to gauge their effect on the performance of herders vis-à-vis others and the overall market efficiency through simulation based approach. The data used for the study has been developed in Python and linear models are estimated using R.

Herding decreases total surplus in private value double auctions, but herders are not worse off than other agents and perform equally in common value auctions. Further, herders and random offerers reduce payoffs of other agents as well, and herding effects the surplus per transaction and not the quantum.

This study explores herding as a strategic behaviour coexisting with rationality and other strategies in specific circumstances. It presents intriguing findings on the impact of herding on individual outcomes and market efficiency, raising new avenues for future research. Implication to research includes a dent on the “sieve” argument of markets rooting out irrationality and from it, a policy implication that follows is the need for corrective measures as markets cannot self-correct this, given herders do not perform worse than others.

The study links the phenomenon of herding to the dynamics of social networks and heuristic-based learning mechanisms that sets apart this research from the majority of existing literature, which predominantly conceptualizes herding as an outcome derived from a perfect Bayesian Equilibrium and a rational learning process.

This study aims to investigate the impact of facial-based perceived trustworthiness on stock valuation, particularly, in the initial public offering (IPO). IPO settings provide the opportunity to investigate whether information asymmetry resulting from company newness in the market would influence the incorporation of soft information in the form of executive facial trustworthiness in stock valuation.

We use a recent machine learning algorithm to detect facial landmarks and then calculate a composite facial trustworthiness measure using several facial features that have previously been observed in neuroscience and psychological studies to be the most determining factor of perceived trustworthiness. We then regress the facial trustworthiness of IPO firm executives to IPO underpricing.

Utilizing machine learning algorithms, we find that the facial trustworthiness of the company executive negatively impacts the extent of IPO underpricing. This result implies that investors incorporate the facial trustworthiness of company executives into stock valuation. The IPO underpricing also shows that the cost of equity is higher when perceived trustworthiness is low. With regard to the higher information asymmetry in IPO transactions, such a negative impact implies the role of facial trustworthiness in alleviating information asymmetry.

This study provides evidence of the impact of top management personal characteristics on firms’ financial transactions in the Indonesian context. From the perspective of investors and other fund providers, this study shows evidence that heuristics still play an important role in financial decision-making. This is also an indication of investor reliance on soft information. Our research method also provides a new opportunity for the use of machine-learning algorithms in processing non-conventional types of data in finance research, which is still relatively rare in emerging markets like Indonesia. To the best of our knowledge, our study is the first to use personalized measures of trust generated through machine-learning algorithms in IPO settings in Indonesia.

Innovation quality is a critical component of enterprise innovation. Prior research primarily focuses on company-level and external policy-level factors that affect innovation quality, while ignoring social-level factors. Based on institutional isomorphism theory, this study examines how the innovation quality of three-dimensional institutional equivalence, which is an important and unique reference group for firms to follow the “law of imitation of close preference”, affects the likelihood of firms' innovation quality.

This study conducts firm random effects and industry/year fixed effects models using China's listed companies from 2002 to 2021.

This study finds that compared with the innovation quality of its other industry, community, or network peers, the innovation quality of three-dimensional institutional equivalence has a greater impact on firm innovation quality. Furthermore, technological intensity significantly increases the effect of three-dimensional institutional equivalence on focal company innovation quality, while financing constraints significantly attenuate this effect. Additionally, when there is no institutional equivalent, the innovation quality of network, industry, and community peers has significant positive effects on enterprise innovation quality. Heterogeneity analysis also indicates that, under the conditions of non-state-owned enterprises, a low regional legal environment, or low regional factor market development, three-dimensional institutional equivalence contributes significantly to firm innovation quality.

This study focuses on the effect of three-dimensional institutional equivalence on Chinese enterprises' innovation quality. Nonetheless, research samples from other countries are not considered in this study.

This study explores the impact of three-dimensional institutional equivalence on firm innovation quality within a systematic theoretical framework and incorporates firm attributes into this framework.

The recent livestreaming commerce has magnified the role of influencer marketing, where the influencers are partnering with brands for product promotion. This study examines the impact of influencer attributes, interaction strategies and parasocial relationships on impulsive buying in livestreaming commerce.

A survey with 368 livestreaming commerce users was analyzed using the symmetric-thinking approach – partial least squares structural equation modeling (PLS-SEM) and asymmetric thinking approach – fuzzy set qualitative comparative analysis (fsQCA).

The results of PLS-SEM indicate that influencer trustworthiness, influencer interactivity and self-disclosure determine parasocial relationships, which in turn influence impulsive buying. The fsQCA finding returned three configurations with various combinations of the causal conditions (i.e. influencer attributes, interaction strategies, parasocial relationships, perceived fit uncertainty and perceived quality uncertainty) explaining the formation of impulsive buying.

These findings provide unique linear and nonlinear insights to explain the combinatory effects of influencer attributes, interaction strategies, parasocial relationships, perceived fit uncertainty and perceived quality uncertainty on impulsive buying in livestreaming commerce.

This study aims to explore the dynamic interplay of key resources (i.e. research and development (R&D), advertising and exports) in affecting the performance of USA manufacturing firms. Specifically, the authors examine the dynamic impact of joint resources and predict differential effect scales contingent on firm capabilities.

This study presents a combined multiple regression analysis (MRA)-multilayer perceptron (MLP) neural network modeling and investigates the complex interlinkage of capabilities, resources and performance. As an innovative approach, the MRA-MLP model investigates the effect of capabilities under the combinatory deployment of joint resources.

This study finds that the impact of joint resources and synergistic rents is not uniform but rather distinctive according to the combinatory conditions and that the pattern is further shaped by firm capabilities. Accordingly, besides signifying the contingent aspect of capabilities across a range of resource combinations, the result also shows that managerial sophistication in adaptive resource control is more than a managerial ethos.

The proposed analytic process provides scientific decision support tools with control mechanisms with respect to deploying multiple resources and setting actionable goals, thereby presenting pragmatic benchmarking options to industry managers.

Using the theoretical underpinnings of the resource-based view (RBV) and resource orchestration, this study advances knowledge about the complex interaction of key resources by presenting a salient analytic process. The empirical design, which portrays holistic interaction patterns, adds to the uniqueness of this study of the complex interlinkages between capabilities, resources and shareholder value.

How much variance in firm performance can be attributed to firms’ corporate political activities (CPA)? Under what conditions does CPA contribute to firm performance? To theorize and empirically tackle these questions, we build on the resource-based view (RBV) to theorize how CPA might improve or hinder firm performance, and specifically examine the direct relationship between firms’ investments in lobbying activities and their performance. We also expect firm growth rate to moderate the relationship between lobbying and performance.

We empirically test our hypotheses using large-scale longitudinal panel data from publicly traded US firms from 2008 to 2018.

Our analyses support our predictions of the double-edged sword effect of lobbying on firm performance. Moreover, our results show that this effect is steeper for firms with higher growth rates.

Our study contributes meaningful insights to strategy scholarship on the influence of nonmarket strategies, highlighting the relevance of firm-specific conditions in shaping the performance outcomes of such strategies. In particular, we make a contribution by identifying a nonlinear relationship between lobbying and firm performance, which is amplified in fast-growing firms compared to stagnant ones.

The main objective of this study is to identify the variables influencing consumers' perceptions of sustainable purchasing intentions and the effects such perceptions have on actual sustainable purchasing behavior. This paper aims to develop an understanding of the postmillennial generation's consumption of sustainable products.

A structured questionnaire was used to collect data for quantitative analysis. It involved sampling a total of 251 respondents, which were postmillennials belonging to the twin cities of Pakistan. A series of tests were applied through Smart PLS4 for all the variables, including descriptive statistics and structural equation modeling.

The results revealed that there is a significant relationship of social value and electronic word of mouth with digital media usage (DMU). Whereas, link of functional and emotional value with DMU was insignificant. The results also portrayed that there exists a positive link between DMU and sustainable consumption behavior (SCB). Moreover, green purchase intention moderated the relationship between DMU and SCB.

There exists a research gap on the role of postmillennial behavioral regulation and digital media use, as potential influences on their purchase behavior. Despite the fact that digital media has been shown to influence millennials' purchasing decisions in the past, there is still a reluctance among postmillennials to engage in environmentally friendly practices. Consequently, research is necessary to comprehend sustainable consumer behaviors; especially from an unaddressed Pakistani perspective.

Recent calls in international management (IM) research ask scholars to conduct more context-sensitive research, however; little attention has been paid to the methodological particularities that inform such context sensitivity. This paper aims to addresses this shortcoming by exploring how emic concepts implicate IM research processes during qualitative field studies.

We carried out ethnographic fieldwork in Brazilian subsidiaries of three German multinational enterprises. We relied on the researchers’ experiences and data from a larger research project including 63 semi-structured interviews, 7 focus groups, documents and field notes. Adopting a culturally sensitive and self-reflexive lens, we reflect on the researchers’ experiences in the Brazilian sociocultural context from an interpretive paradigm.

Our findings reveal how seven identified emic concepts affect four prototypical phases of the research process: securing access, collecting data, analyzing data and presenting findings. We discuss how these seven emic concepts influenced the research process and impacted research outcomes, as experienced by the researchers.

Findings are limited by our self-reflexive capabilities as foreign researchers, the limited explanatory power of emic categories, our paradigmatic positioning and the research context.

We contribute to research practice by providing eight suggestions for conducting international fieldwork and proposing avenues for future research.

This research contributes to the epistemological and methodological debate on context-sensitive research by arguing that intercultural sensitivity needs to be managed as an integral dimension for any form of international fieldwork. Findings contribute to interpretive approaches showing how emic concepts affect research practices, with implications for critical management perspectives.

Drawing on the literature on technological acquisition and the knowledge-based view , this study examines how technological overlap between acquiring and target firms influences acquisition premiums. We further explore how the resulting synergies are contingent on the dynamic characteristics of the target firm, specifically its technology clockspeed and industry munificence. Technology clockspeed indicates the pace of technological evolution, reflecting internal dynamic resources, while industry munificence represents the abundance of external resources. These boundary conditions illustrate the dynamics of synergies, explaining their moderation effects on acquisition premiums.

We analyze a sample of 369 technological acquisitions by publicly traded U.S. firms between 1990 and 2011. To test our hypotheses, we used the ordinary least squares regression model with robust standard errors clustered by acquiring firms. In the robustness checks, we applied the generalized estimating equations to account for non-independent observations in our sample and verified that the results were robust to an alternative two-way clustering approach.

We suggest that a low level of technological overlap between an acquiring firm and its target firm leads the acquiring firm to offer a high acquisition premium because of the expected synergistic potential that evolves from combining two distant technological bases. We further find that this effect is contingent on the target firm's technology clockspeed and industry munificence. Specifically, the negative effect is amplified when target firms exhibit a rapid pace of technological evolution, whereas it is weakened when target firms operate in highly munificent industries characterized by robust growth and abundant resource flows.

This study has several limitations, but it offers opportunities for future research. First, our sample is limited to domestic acquisitions between U.S. publicly traded firms, which may restrict generalizability. Cross-border acquisitions could reveal different dynamics, as technology leakage and national security concerns might make technological overlap a more sensitive factor. Additionally, private firms were not included, and their distinct strategic considerations could provide further insights. Future research could explore post-acquisition data to validate these synergies and expand the scope to include international contexts and private firms for a comprehensive analysis.

Our findings highlight important implications for managers in technology sector acquisitions. This study underscores the need for a thorough evaluation of target firms to avoid misjudging synergies. Low technological overlap can heighten expectations for value creation, making it crucial for executives to accurately assess potential synergies to prevent overestimation. Managers should consider both internal resources and external industry conditions when evaluating synergies. Ultimately, these insights help managers offer informed prices that reflect true strategic synergies, adopting effective valuation practices to mitigate risks of financial overpayments and poor post-merger performance.

The social implications of our findings emphasize the broader impact of acquisition decisions on innovation and competition within the technology sector. By ensuring accurate valuation and avoiding overpayment, companies can allocate resources more efficiently, fostering sustainable growth and innovation. This diligent approach can reduce the risk of corporate failures.

This study makes two key theoretical contributions. First, it identifies technological overlap as a critical determinant of acquisition premiums in technological acquisitions, addressing gaps in the literature that focused on CEO characteristics and managerial attention. Second, it expands the theoretical framework by highlighting the dynamic nature of synergies, influenced by the target firm's technology clockspeed and industry munificence. By integrating both acquiring and target firm characteristics, this study provides a relational perspective on value creation, explaining why firms pay high premiums and offering a more comprehensive understanding of the strategic motivations in technological acquisitions.