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Berthon and Pitt (2018) recently highlighted the symbiotic relationship between fake news and brands. This paper aims to draw on semiotics to refine the fake/real news dichotomy to a fourfold typology.

First, the authors turn to semiotics and review Greimas’ (1966) semiotic square. Second, they use this framework to refine the fake/real news dichotomy into a four-fold typology. Third, they illustrate each type with a news report on the topic of climate change. Fourth, they apply this framework to reveal four types of brand: real, fake, empty and ironic.

Given that brand communications are heterogeneous, the authors suggest that the typology can be reconceptualized as dimensions and brands communications decoded accordingly. They conclude by exploring further opportunities offered by the semiotic square for interpretive investigation.

The value of the paper lies in the novel use of the semiotic square to shed light on both news and brand communications.

Privacy considerations have become a topic with increasing interest from academics, industry leaders and regulators. In response to consumers’ privacy concerns, Google announced in 2020 that Chrome would stop supporting third-party cookies in the near future. At the same time, advertising technology companies are developing alternative solutions for online targeting and consumer privacy controls. This paper aims to explore privacy considerations related to online tracking and targeting methods used for programmatic advertising (i.e. third-party cookies, Privacy Sandbox, Unified ID 2.0) for a variety of stakeholders: consumers, AdTech platforms, advertisers and publishers.

This study analyzes the topic of internet user privacy concerns, through a multi-pronged approach: industry conversations to collect information, a comprehensive review of trade publications and extensive empirical analysis. This study uses two methods to collect data on consumer preferences for privacy controls: a survey of a representative sample of US consumers and field data from conversations on web-forums created by tech professionals.

The results suggest that there are four main segments in the US internet user population. The first segment, consisting of 26% of internet users, is driven by a strong preference for relevant ads and includes consumers who accept the premises of both Privacy Sandbox and Unified ID (UID) 2.0. The second segment (26%) includes consumers who are ambivalent about both sets of premises. The third segment (34%) is driven by a need for relevant ads and a strong desire to prevent advertisers from aggressively collecting data, with consumers who accept the premises of Privacy Sandbox but reject the premises of UID 2.0. The fourth segment (15% of consumers) rejected both sets of premises about privacy control. Text analysis results suggest that the conversation around UID 2.0 is still nascent. Google Sandbox associations seem nominally positive, with sarcasm being an important factor in the sentiment analysis results.

The value of this paper lies in its multi-method examination of online privacy concerns in light of the recent regulatory legislation (i.e. General Data Protection Regulation and California Consumer Privacy Act) and changes for third-party cookies in browsers such as Firefox, Safari and Chrome. Two alternatives proposed to replace third-party cookies (Privacy Sandbox and Unified ID 2.0) are in the proposal and prototype stage. The elimination of third-party cookies will affect stakeholders, including different types of players in the AdTech industry and internet users. This paper analyzes how two alternative proposals for privacy control align with the interests of several stakeholders.

The purpose of this research is to present an integrated methodological framework to aid in performance stewardship of management institutions according to their strategies based on a holistic evaluation encompassing social, economic and environmental dimensions.

A Mamdani fuzzy inference system (FIS) approach was adopted to design the quantitative models with respect to balanced scorecard (BSC) perspectives to demonstrate dynamic capability. Individual models were developed for each perspective of BSC using Mamdani FIS. Data was collected from subject matter experts in management education.

The proposed methodology is able to successfully compute the scores for each perspective. Effective placement, teaching learning process, faculty development and systematic feedback from the stakeholders were found to be the key drivers for revenue generation. The model is validated as the results were well accepted by the head of the institution after implementation.

The model resulting from this study will assist the institution to cyclically assess its performance, thus enabling continuous improvement. The strategy map provides the causality of the objectives across the four perspectives to aid the practitioners to better strategize. Also this study contributes to the literature of BSC as well to the applications of multi-criteria decision-making (MCDM) techniques.

Mamdani FIS integrated BSC model is a significant contribution to the academia of management education to quantitatively compute the performance of institutions. This quantified model reduces the ambiguity for practitioners to decide the performance levels for each metric and the priorities of metrics.

This paper aims to investigate the relationships between participative decision-making, ethical leadership and leadership performance, which might make school leaders quit autocratic behavior and enhance their performance at private K12 schools in Iraq.

The researchers collected data through a questionnaire using a stratified sampling methodology from 207 educators of 10 institutions. The research methodology included demographic analysis, factor analysis, structural equation modeling and mediation analysis.

The participative decision-making affected moral, knowledge and attitude that contributed to leadership performance. Besides, the only attitude mediated the relationship between participative decision-making and leadership performance.

The study is limited to private K12 schools in Iraq. Therefore, the findings cannot be generalized. It might guide educational institutes to change their management style.

The study delivers a unique insight into education in Iraq.

This study aims to develop a resilient contractor selection model that also considers community concerns in post-disaster reconstruction projects using a “build-back better (BBB)” approach.

At the outset, a comprehensive literature review was conducted to develop the model. During this literature review, a set of contractor selection criteria were identified. Focus group discussion (FGD) sessions were then organized to revise and refine the identified criteria. As a result, a final list of 39 selection criteria was developed. Next, the Bayesian best worst method (BBWM) was conducted to determine the weights of each selection criterion. Finally, the proposed model was validated by conducting a hypothetical case study and fuzzy VlseKriterijuska Optimizacija I Komoromisno Resenje (fuzzy VIKOR) analysis. Moreover, a sensitivity analysis was conducted to examine the effect of the maximum group utility (v) value in the model.

The results emphasized that contractors in post-disaster reconstruction projects cannot be selected merely based on “technical” and “economic” factors. Instead, the other aspects, namely “organizational and managerial,” “environmental sustainability,” “resource management and procurement” and “end-user,” should also be taken into consideration. Second, factors related to financial strength, experience, risk management, energy efficiency, resource availability and assurance were particularly deemed the most significant, needing the detailed attention of the decision-makers. Lastly, the case study revealed that the proposed model has a significant potential to systemize contractor selection processes in post-disaster reconstruction projects.

Disasters, which are increasing in frequency and severity today, devastate the community’s environmental, economic and social conditions. Post-disaster reconstruction projects commence rapidly after a disaster for recovery. However, poor management procedures in these projects trigger time and cost overruns. Unlike traditional construction projects, post-disaster reconstruction projects are distinctive due to the uncertainties caused by the disasters and the prioritization of community concerns. Therefore, contractors should be selected in a way that can meet the specific needs of reconstruction projects. Otherwise, resilience in the built environment and community satisfaction can hardly be enhanced. Accordingly, this study is one of the first attempts to develop a contractor selection model for post-disaster reconstruction projects. It is believed that the developed model will make essential theoretical and practical contributions to the post-disaster reconstruction domain.

This study aims to propose a method known as the fuzzy technique for order preference by similarity to ideal solution (fuzzy TOPSIS) for complex project selection in organizations. To fulfill study objectives, the factors responsible for making a project complex are collected through literature review, which is then analyzed by fuzzy TOPSIS, based on three decision-makers’ opinions.

The selection of complex projects is a multi-criteria decision-making (MCDM) process for global organizations. Traditional procedures for selecting complex projects are not adequate due to the limitations of linguistic assessment. To crossover such limitation, this study proposes the fuzzy MCDM method to select complex projects in organizations.

A large-scale engine manufacturing company, engaged in the energy business, is studied to validate the suitability of the fuzzy TOPSIS method and rank eight projects of the case company based on project complexity. Out of these eight projects, the closeness coefficient of the most complex project is found to be 0.817 and that of the least complex project is found to be 0.274. Finally, study outcomes are concluded in the conclusion section, along with study limitations and future works.

The outcomes from this research may not be generalized sufficiently due to the subjectivity of the interviewers. The study outcomes support project managers to optimize their project selection processes, especially to select complex projects. The presented methodology can be used extensively used by the project planners/managers to find the driving factors related to project complexity.

The presented study deliberately explained how complex projects in an organization could be select efficiently. This selection methodology supports top management to maintain their proposed projects with optimum resource allocations and maximum productivity.

Supplier selection (SS) is one of the prime competencies in a sourcing decision. Taking into account the key role played by suppliers in facilitating the implementation of green supply chain management (GSCM), it is somewhat surprising that very little research attention has been imparted to the development of a strategic sourcing model for GSCM. This research aims to develop a strategic sourcing framework in which supplier organizations are prioritized and ranked based on their GSCM performance. Accordingly, the benchmark organization is identified and its strategy is explored for GSCM performance improvement.

The research develops an innovative GSCM performance evaluation framework using six parameters, namely, investment in corporate social responsibility, investment in research and development, utilization of renewable energy, total energy consumption, total carbon-di-oxide emissions and total waste generation. An integrated multicriteria decision-making (MCDM) approach is proposed in which the entropy method calculates criteria weights. The Complex Proportional Assessment (COPRAS) and the Grey relational analysis (GRA) methods are used to rank supplier organizations based on their performance scores. A real-world case of green supplier selection (GSS) is considered in which five leading India-based automobile manufacturing organizations (Supplier 1, Supplier 2, Supplier 3, Supplier 4 and Supplier 5) are selected. Surveys with industry experts at the strategic, tactical, and operational levels are carried out to collect relevant data.

The results reveal that total carbon dioxide emission is the most influential parameter, as it gains the highest weight. On the contrary, investment in research and development, and total waste generation have no significant impact on GSCM performance. Results show that Supplier 5 secures the top rank. Hence, it is the benchmark organization.

The proposed methodology offers an easy and comprehensive approach to sourcing decisions in the field of GSCM. The entropy weight-based COPRAS and GRA methods offer an error-free channel of decision-making and can be proficiently used to outrank various industrial sectors based on their GSCM performances. This research is specific to the automobile manufacturing supply chain. Therefore, research outcomes may vary across supply chains with distinct characteristics.

The basic propositions of this research are based on a real-world case. Hence, the research findings are practically feasible. The less significant parameters identified in this study would enable managers to impart more attention to vulnerable areas for improvement. This research may help policymakers identify the influential parameters for effective GSCM implementation. As this research considers all aspects of sustainability, the strategies of the benchmark supplier have a direct impact on organizations' overall sustainability. The study would enable practitioners to make various strategies for GSCM performance improvement and to develop a cleaner production system.

The originality of this research lies in the consideration of both economic, social, environmental and operational aspects of sustainability for assessing the GSCM performance of supplier organizations. Quantitative criteria are considered so that vagueness can be removed from the decision. The use of an integrated grey-based approach for developing a strategic sourcing model is another unique feature of this study.