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Grey target decision-making serves as a pivotal analytical tool for addressing dynamic multi-attribute group decision-making amidst uncertain information. However, the setting of bull's eye is frequently subjective, and each stage is considered independent of the others. Interference effects between each stage can easily influence one another. To address these challenges effectively, this paper employs quantum probability theory to construct quantum-like Bayesian networks, addressing interference effects in dynamic multi-attribute group decision-making.

Firstly, the bull's eye matrix of the scheme stage is derived based on the principle of group negotiation and maximum satisfaction deviation. Secondly, a nonlinear programming model for stage weight is constructed by using an improved Orness measure constraint to determine the stage weight. Finally, the quantum-like Bayesian network is constructed to explore the interference effect between stages. In this process, the decision of each stage is regarded as a wave function which occurs synchronously, with mutual interference impacting the aggregate result. Finally, the effectiveness and rationality of the model are verified through a public health emergency.

The research shows that there are interference effects between each stage. Both the dynamic grey target group decision model and the dynamic multi-attribute group decision model based on quantum-like Bayesian network proposed in this paper are scientific and effective. They enhance the flexibility and stability of actual decision-making and provide significant practical value.

To address issues like stage interference effects, subjective bull's eye settings and the absence of participative behavior in decision-making groups, this paper develops a grey target decision model grounded in group negotiation and maximum satisfaction deviation. Furthermore, by integrating the quantum-like Bayesian network model, this paper offers a novel perspective for addressing information fusion and subjective cognitive biases during decision-making.

With respect to multi-stage group risk decision-making problems in which all the attribute values take the form of grey number, and the weights of stages and decision makers are unknown, the purpose of this paper is to propose a new decision-making method based on grey target and prospect theory.

First, the sequencing and distance between two grey numbers are introduced. Then, a linear operator with the features of the “rewarding good and punishing bad” is presented based on the grey target given by decision maker, and the prospect value function of each attribute based on the zero reference point is defined. Next, weight models of stages and decision makers are suggested, which are based on restriction of stage fluctuation, the maximum differences of alternatives and the maximum entropy theory. Furthermore, the information of alternatives is aggregated by WA operator, the alternatives are selected by their prospect values.

The comprehensive cumulative prospect values are finally aggregated by WA operator, alternatives are selected or not are judged by the sign of the comprehensive prospect theory, if the prospect value of alternative is negative, the corresponding alternative misses the group decision makers’ grey target, on the contrary, if the prospect value of alternative is positive, the corresponding alternative is dropped into the group decision makers’ grey target, the alternative with positive prospect value whose value is the maximum is selected.

Compared with the traditional decision-making methods using expected utility theory which suppose the decision makers are all completely rational, the proposed method is based on irrational which is more in line with the decision maker’s psychology. And this method considers the decision maker’s psychological expectation values about every attribute, different satisfactory grey target about attributes will directly affect decision-making result.

This study aims to examine the interaction effects of chatbots’ language style and customers’ decision-making journey stage on customer’s service encounter satisfaction and the mediating role of customer perception of emotional support and informational support using the construal level theory and social support theory as conceptual frameworks.

This study used a scenario-based experiment with a 2 (chatbot’s language style: abstract language vs concrete language) × 2 (decision-making journey stage: informational stage vs transactional stage) between-subjects design.

Findings show that during the informational stage, chatbots that use abstract language style exert a strong influence on service encounter satisfaction through emotional support. During the transactional stage, chatbots that use concrete language style exert a strong impact on service encounter satisfaction through informational support.

Findings provide some suggestions for improving customer–chatbot interaction quality during online service encounters.

This study offers a novel perspective on customer interaction experience with chatbots by investigating the chatbot’s language styles at different decision-making journey stages.

Families and households make up a significant proportion of the real estate market. There is, however, little information in mainstream real estate literature on the impact of family behaviour on real estate decisions. This paper clarifies some of these issues by analysing and expanding on many of the findings from the marketing literature, in particular the topic of influence between different family members in the purchase of a new home. This paper presents some important issues to be considered when examining family decision‐making. These include the roles played by different family members and their influence at different stages of the decision‐making process. It also reports on the findings of a study involving a series of in‐depth interviews with real estate agents to determine their perception of the family decision‐making process in relation to a house purchase decision. This culminates in a conceptual framework on family decision making specifically for the purchase of residential real estate, before discussing the implications of these findings to the general real estate market, including service, promotion and valuation.

The purpose of this paper is to examine the customer decision-making journey of high involvement female fashion consumers in the context of omnichannel fashion retailing.

The research is qualitative in nature, using a multi-method approach consisting of focus groups, semi-structured interviews, online diaries and follow-up interviews, with grounded theory applied to analyse the data.

The results of the study include a framework to outline the stages of the omnichannel customer decision-making journey for young high involvement female fashion consumers. The findings also reveal that an omnichannel decision-making journey is the one that predicated on risk and that consumers employ specific strategies to avoid such risks.

Due to the nature of this research, the sample size is limited and may not be generalised. Data collection was confined to Manchester, UK.

Customer journey mapping enables practitioners to view the entire shopping experience through the eyes of the customer and enables retailers' fault-find issues within the customer and brand experience.

The paper advances knowledge about fashion and consumer behaviour. The customer decision journey framework maps the emotional experiences, devices and channels encountered by high-involvement fashion consumers across each stage of the omnichannel journey.

Lawrence Kohlberg's (1969) concept of cognitive moral development (CMD) has been one of the most investigated constructs in the field of social psychology, with over one thousand studies reported investigating this construct in only two decades of research. However, what is the relationship of this theoretical construct to actual decision making and behavior? Blasi (1980, p. 4) opined for the criticality of moral judgement research to both ethical decision making and ethical inquiry, stating that “without judgement, an action, no matter how beneficial, would not be moral.” Relating Kohlberg's model to business decision making and behavior has been central to the building of theoretical frameworks of the ethical decision making process engaged in by individuals. The models of this process proposed by Trevino and Youngblood (1990), Trevino (1986), Bommer, Gratto, Gravender, and Tuttle (1987), Ferrell and Gresham (1985), Ferrell, Gresham, and Fraedrich (1989), Swinyard, DeLong, and Cheng (1989), and Jones (1991) all contained cognitive moral development as a factor in their respective models of ethical decision making.

Practitioners in particular have noted that kids are growing older younger (KGOY) and academic research has in parallel shown that children are becoming more involved in the final stages of purchase decisions, albeit in a limited number of product categories studied. This paper aims to investigate this market.

This quantitative and qualitative study examines the relatively under‐researched, but increasingly important, tweenager market across a number of product categories and the extent to which ten to 12 year olds are involved in the final stages of purchase decision making. Further to this, the paper considers whether a liberal versus traditional approach to decisions made within the family (gender role orientation (GRO)) affects the degree of involvement.

The findings suggest that GRO is indeed a factor in family decision making but that the relationship is far from a simple one. The authors posit why perceptions of involvement are sometimes inconsistent and why some kids may not be growing older younger in the way previously thought, but may simply believe they are more involved in purchase decision making as a consequence of parental strategies as well as the influences of media, school and peers.

The paper describes the implications for marketing practitioners and academic researchers.

The purpose of this paper is to construct a dynamic information aggregation decision-making model based on variable precision rough set.

To deal with the dynamic decision-making problems, the grey relational analysis method, grey fixed weight clustering based on the centre triangle whitening weight function and maximum entropy principle is used to establish the dynamic information aggregation decision-making model based on variable precision rough set. The method, to begin with, the grey relational analysis method is used to determine the attributes weights of each stage; taking the proximity of the attribute measurement value and positive and negative desired effect value and the uncertainty of time weight into account, a multi-objective optimisation model based on maximum entropy principle is established to solve the model with Lagrange multiplier method, so that time weights expression are acquired; what is more, the decision-making attribute is obtained by grey fixed weight clustering based on the centre triangle whitening weight function, so that multi-decision-making table with dynamic characteristics is established, and then probabilistic decision rules from multi-criteria decision table are derived by applying variable precision rough set. Finally, a decision-making model validates the feasibility and effectiveness of the model.

The results show that it the proposed model can well aggregate the multi-stage dynamic decision-making information, realise the extraction of decision-making rules.

The method exposed in the paper can be used to deal with the decision-making problems with the multi-stage dynamic characteristics, and decision-making attributes contain noise data and the attribute values are interval grey numbers.

The paper succeeds in realising both the aggregation of dynamic decision-making information and the extraction of decision-making rules.

In a bid to broaden the understanding of the real estate investment decision-making framework, the purpose of this paper is to examine the real estate asset allocation decision-making practices of real estate funds in Nigeria, a developing economy. This is with a view to providing information toward enhancing real estate investment decisions.

A mixed-methods approach comprising a combination of literature review, expert interviews and semi-structured questionnaire survey is adopted for this study. Through literature review and expert interviews, the asset allocation decision-making process of institutional real estate funds was identified. Based on the literature review and expert discussions, a semi-structured questionnaire was developed and self-administered on fund/portfolio managers of 59 institutional real estate funds in Nigeria to investigate their asset allocation decision-making practice. Data were analyzed using descriptive and inferential statistics for the closed-ended questions while the open-ended questions were content analyzed.

The findings revealed that the asset allocation decision-making process utilized by public and private real estate funds follows an opportunistic asset accumulation approach. The decision-making process also varies depending on the nature of the fund. Further findings showed that government policies, political uncertainties and regulatory mechanism motivate asset allocation decisions. Moreover, majority of the sampled real estate funds employed a combination of in-house personnel and external consultants (hybrid), while mean/standard deviation and cash flow analysis (DCF, NPV) were mostly utilized by the funds in making property investment decisions.

The findings implied that the real estate asset allocation decision-making process of institutional property investors in Nigeria deviates from the normative model of the asset allocation process prescribed in the literature and varies depending on the nature of the real estate funds. As such, familiarization of institutional investors with government policies, political climate and other regulatory mechanism (barriers to entry) guiding the ownership and operation of real estate assets in the country could improve their real estate investment decisions.

The study complements and extends existing literature on real estate asset allocation decision-making process of institutional investors from the viewpoint of the actors involved in a developing African economy.

By acknowledging the importance of micro-influencers and all decision-making process stages, this study aims to explore the impact of perceived influencer’s credibility, impacted by the sponsorship absenteeism, on problem recognition, information search, alternative evaluation, purchase and post-purchase. Additionally, the authors investigate the moderating role of trust level on the researched relationships.

This study focuses on 111 young Croatian consumers of cosmetic products. The authors analysed data with confirmatory factor and regression analyses.

This study reveals positive relationships between micro-influencers’ perceived credibility and all decision-making phases. The research results also show that the lack of sponsorship positively influences perceived credibility. Furthermore, results indicate that the trust level is an essential moderator for the relationships between perceived credibility and sponsorship and information search and buying stages.

Limitations include the convenience sampling method and data collection at one point while also focusing on consumers from one country.

This study provides practical implications for companies outlining the marketing activities that should be considered in all stages of the decision-making process while recognising the attractiveness of micro-influencers for the buying experience.

This study fills gaps in the literature on micro-influencers credibility in general and particularly in the cosmetics industry. In addition, the study fills the gaps in the literature considering the impact of perceived micro-influencer credibility on all five decision-making process stages.