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This study aims to investigate organizational learning, represented by the absorptive capacity, as a condition for the firm to learn about marketing data and make more informed decisions. The authors also aimed to understand how the behavior of micro, small and medium enterprises (MSME) businesses differ in this scenario through a multilevel perspective.

Placing absorptive capacity as a mediator of the relationship between business analytics and rational marketing decisions, the authors analyzed data from 224 Brazilian retail companies using structural equation modeling estimated with partial least squares. To test the cross-level moderation effect, the authors also performed a multilevel analysis in RStudio.

The authors found a partial mediation of the absorptive capacity in the relation between business analytics and rational marketing decisions. The authors also discovered that, in the MSMEs firms’ group, even if smaller companies find it more difficult to use data, those that do may reap more benefits than larger ones. This is due to the influence of size in how firms handle information.

The sample size, despite having shown to be consistent and valid, is considered small for a multilevel study. This suggests that our multilevel results should be viewed as suggestive, rather than conclusive, and subjected to further validation.

Rather than solely positioning business analytics as a tool for decision support, the authors’ analysis highlights the importance for firms to develop the absorptive capacity to enable ongoing acquisition, exploration and management of knowledge.

MSMEs are of economic and social importance to most countries, especially developing ones. This research aimed to improve understanding of how this group of firms could transform knowledge into better decisions. The authors also highlight micro and small firms’ difficulties with the use of marketing data so that they can have more effective practices.

The research contributes to the understanding of organizational mechanisms to absorb and learn from the vast amount of current marketing information. Recognizing the relevance of MSMEs, a preliminary multilevel analysis was also conducted to comprehend differences within this group.

The purpose of this study is to examine the behaviour of retail investors while making an investment decision and how it gets affected by the behavioural biases of the investors using a moderated-mediation framework.

A mixed method approach has been used to fulfil the objectives of the study. In the first study, a qualitative analysis of the interviews with 15 retail investors was conducted. As part of the quantitative study, a total of 201 responses from Indian retail investors were collected using systematic sampling and analysed using structural equation modelling and Process Macro.

The results indicate that anchoring bias, availability bias, herding bias, switching cost, sunk cost, regret avoidance and perceived threat have a significant effect on retail investors’ investing intention. The attitude of the investors towards investing decisions mediates the effects of behavioural bias and the status quo on investment intention. The results of the moderated-mediation analysis indicate that mediating effect of attitude varied at the low and high-risk aversion of investors.

The findings of this study will help regulators and retail investors to understand the critical behavioural biases which affect the investors’ investing intention.

The paper contributes to the literature on investors’ behaviour, status quo bias theory (SQB) and behavioural bias. This study uniquely proposes a moderated-mediation framework to understand the effects of biases on retail investors’ investment intention.

Following behavioral finance and monetary wisdom, the authors theorize: Decision-makers (investors) adopt deep-rooted personal values (the love-of-money attitudes/avaricious financial aspirations) as a lens to frame critical concerns (short-term and long-term investment decisions) in the immediate-proximal (current income) and distal-omnibus (future inheritance) contexts to maximize expected utility and ultimate serenity across context, people and time.

The authors collected data from 277 active equity traders (professional money managers and individual investors) in Pakistan’s two most robust investment hubs—Karachi and Lahore. The authors measured their love-of-money attitude (avaricious monetary aspirations), short-term and long-term investment decisions and demographic variables and collected data during Pakistan's bear markets (Pakistan Stock Exchange, PSX-100).

Investors’ love of money relates to short-term and long-term decisions. However, these relationships are significant for money managers but non-significant for individual investors. Further, investors’ current income moderates this relationship for short-term investment decisions but not long-term decisions. The intensity of the aspirations-to-short-term investment relationship is much higher for investors with low-income levels than those with average and high-income levels. Future inheritance moderates the relationships between aspirations and short-term and long-term decisions. Regardless of their love-of-money orientations, investors with future inheritance have higher magnitudes of short-term and long-term investments than those without future inheritance. The intensity of the aspirations-to-investments relationship is more potent for investors without future inheritance than those with inheritance. Investors with low avaricious monetary aspirations and without inheritance expectations show the lowest short-term and long-term investment decisions. Investors' current income and future inheritance moderate the relationships between their love of money attitude and short-term and long-term decisions differently in Pakistan's bear markets.

The authors help investors make financial decisions and help financial institutions, asset management companies, brokerage houses and investment banks identify marketing strategies and investor segmentation and provide individualized services.

Professional money managers have a stronger short-term orientation than individual investors. Lack of wealth (current income and future inheritance) motivates greedy investors to take more risks and become more vulnerable than non-greedy ones—investors’ financial resources and wealth matter. The Matthew Effect in investment decisions exists in Pakistan’s emerging economy.

The Internet has changed consumer decision-making and influenced business behaviour. User-generated product information is abundant and readily available. This paper argues that user-generated content can be efficiently utilised for business intelligence using data science and develops an approach to demonstrate the methods and benefits of the different techniques.

Using Python Selenium, Beautiful Soup and various text mining approaches in R to access, retrieve and analyse user-generated content, we argue that (1) companies can extract information about the product attributes that matter most to consumers and (2) user-generated reviews enable the use of text mining results in combination with other demographic and statistical information (e.g. ratings) as an efficient input for competitive analysis.

The paper shows that combining different types of data (textual and numerical data) and applying and combining different methods can provide organisations with important business information and improve business performance.

The paper shows that combining different types of data (textual and numerical data) and applying and combining different methods can provide organisations with important business information and improve business performance.

The study makes several contributions to the marketing and management literature, mainly by illustrating the methodological advantages of text mining and accompanying statistical analysis, the different types of distilled information and their use in decision-making.

This paper aims to explore the challenges and opportunities faced by buying centers in small and medium enterprises (SME) manufacturing companies in view of recent technological changes and the virtualization of communication.

This study uses a qualitative approach with multiple case studies to portray complex realities within the buying centers in the manufacturing SME context. The authors selected five Italian companies to portray the diverse characteristics, practices and policies of relevant stakeholders before reaching saturation with the issues explored.

The authors find that interactions among buying center members are more effective with greater collaboration and exchange (as opposed to competition and a struggle for power). Virtual/hybrid relations require greater intra-group cooperation, whereas diverse backgrounds and collaborative interactions help the flexibility and performance of the buying center. Greater use of technology produces certainty and automation, but it may also cause overload and biases that can be solved with the ability to analyze and clear responsibility for decisions.

The authors studied only five Italian companies in this study. Future research in other countries with diverse cultural and socio-economic conditions and methods would help extend this research.

The findings would improve the understanding of the challenges of adopting new purchase process technologies that would help automate routine tasks, produce useful data and support decision-making.

Unlike prior studies, this study uses an exploratory design to study the evolution of buying centers in SMEs to seek deeper insights into the challenges and opportunities faced by SMEs because of the growing use of emerging technologies.

This study aims to conduct a bibliometric analysis to provide a comprehensive picture and identify future research directions to enrich the existing literature on behavioral biases.

The data set comprises 518 articles from the Web of Science database. Performance analysis is used to highlight the significant contributors (authors, institutions, countries and journals) and contributions (highly influential articles) in the field of behavioral biases. In addition, network analysis is used to delve into the conceptual and social structure of the research domain.

The current review has identified four major themes: “Influence of behavioral biases on investment decisions,” “Determinants of home bias,” “Impact of biases on stock market variables” and “Investors’ decision-making under uncertainty.” These themes reveal that a majority of studies have focused on equity markets, and research on other asset classes remains underexplored.

This study extracted data from a single database (Web of Science) to ensure standardization of results. Consequently, future research could broaden the scope of the bibliometric review by incorporating multiple databases.

The novelty of this research is to provide valuable guidance by evaluating the existing literature and advancing the knowledge base on the conceptual and social structure of behavioral biases.

This paper delves into evaluating the effectiveness of warning messages as a deterrent against excessive fat consumption. It examines how consumers perceive the fat content of food products when presented with two distinct label types: (1) a textual warning, providing succinct information about the fat content, and (2) a pictorial warning, offering a visual representation that immediately signifies the fat content.

Two quantitative studies were carried out. Study 1 employed a questionnaire to evaluate the efficacy of textual and pictorial warning messages on high- and low-fat food products. Similarly, Study 2 replicated this comparison while incorporating a neuromarketing instrument to gauge participants’ cerebral reactions.

Results indicate that pictorial warnings on high-fat foods significantly deter consumers’ purchasing intentions. Notably, these pictorial warnings stimulate the left prefrontal area of the cerebral cortex, inducing negative emotions in consumers and driving them away from high-fat food items.

While the influence of images over text in shaping consumer decisions is well understood in marketing, this study accentuates the underlying mechanism of such an impact through the elicitation of negative emotions. By understanding this emotional pathway, the paper presents fresh academic and managerial perspectives, underscoring the potency of pictorial warnings in guiding consumers towards healthier food choices.

1. Textual warnings do not seem to discourage high-fat product consumption.

2. A pictorial warning represents the fat content of an equivalent product.

3. Pictorial warnings decrease the intention to purchase a high-fat product.

4. Pictorial warnings determine an increase in negative emotions.

Textual warnings do not seem to discourage high-fat product consumption.

A pictorial warning represents the fat content of an equivalent product.

Pictorial warnings decrease the intention to purchase a high-fat product.

Pictorial warnings determine an increase in negative emotions.

Although businesses continue to take up artificial intelligence (AI), concerns remain that companies are not realising the full value of their investments. The study aims to provide insights into how AI creates business value by investigating the mediating role of Business Process Management (BPM) capabilities.

The integrative model of IT Business Value was contextualised, and structural equation modelling was applied to validate the proposed serial multiple mediation model using a sample of 448 organisations based in the EU.

The results validate the proposed serial multiple mediation model according to which AI adoption increases organisational performance through decision-making and business process performance. Process automation, organisational learning and process innovation are significant complementary partial mediators, thereby shedding light on how AI creates business value.

In pursuing a complex nomological framework, multiple perspectives on realising business value from AI investments were incorporated. Several moderators presenting complementary organisational resources (e.g. culture, digital maturity, BPM maturity) could be included to identify behaviour in more complex relationships. The ethical and moral issues surrounding AI and its use could also be examined.

The provided insights can help guide organisations towards the most promising AI activities of process automation with AI-enabled decision-making, organisational learning and process innovation to yield business value.

While previous research assumed a moderated relationship, this study extends the growing literature on AI business value by empirically investigating a comprehensive nomological network that links AI adoption to organisational performance in a BPM setting.

This article aims to explore the impact of interpersonal relationship stimuli and click-like on purchase intention across different generations of bank customers, with a focus on the moderating effect of online trust.

The sample consists of 435 online bank customers from the Facebook community and the data collection was conducted using an online survey method. The model estimation utilized the partial least squares technique, along with multigroup analysis and importance-performance map analysis.

The empirical evidence supports the hypothesized relationships between interpersonal relationship stimuli, click-like and purchase intention, but varies across different generations and is contingent upon online trust. The analysis reveals commonalities in how Generation Z, Millennials and Generation X respond to interpersonal relationship stimuli while exhibiting distinct responses to click-like.

The empirical evidence confirms the hypothesized relationships between interpersonal relationship stimuli, click-like and purchase intention. However, these relationships exhibit variations across different generations and are contingent upon the level of online trust. The analysis highlights shared responses to interpersonal relationship stimuli among Generation Z, Millennials and Generation X, while also revealing distinct reactions to click-like within these generational groups.

This research investigates the collective impact of interpersonal relationship stimuli and click-like on purchase intention, taking into account the moderating role of online trust within various generational cohorts in the banking sector.

The purpose of this study is to investigate the role of consumers’ moral preferences between moral and economic benefits and consumers’ moral and rational behaviour intentions based on moral decision-making models of previous studies.

Respondents were asked to answer a questionnaire measuring moral and economic benefits, consumers’ moral preferences and moral and rational behaviour intention after reading a stimulus describing imaginary fashion brand A’s unethical activities.

Moral and economic benefits directly and significantly affect moral and rational behaviour intention. Homo economicus evoked by an economic benefit had a negative effect on moral behaviour intention.

This study focused only on a moral benefit and an economic benefit as factors evoking consumers’ moral preferences. This study was also conducted only in a Korean context and considered a specific industry. In future research, the results of this study should be extended to design the “possibility of punishment” to encourage moral behaviour by discouraging the effect of homo economicus. The results have implications for companies such as social enterprises and charities that want to promote consumers’ moral behaviour.

This study provides evidence on why ethical consumers do not always make ethical decisions by confirming that homo economicus has a significant influence on not only rational behaviour intention but also moral behaviour intention.