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Book part
Publication date: 14 December 2023

Joshua Doyle

The theory of third order inference is a theory of how cultural beliefs influence individuals' decisions under conditions of interdependence and uncertainty. In this study, I…

Abstract

Purpose

The theory of third order inference is a theory of how cultural beliefs influence individuals' decisions under conditions of interdependence and uncertainty. In this study, I build on prior work extending the theory to the role of third order information on social trust in public goods dilemmas. Namely, I argue that when second order information on the beliefs of those relevant to the group task are present, this information should influence decision-making over first and third order.

Methodology

I test this argument in an experimental public goods game. After measuring first order social trust, participants are randomly sorted into one of four conditions – two that pair third and second order information on social trust as parallel and two that pair them as in conflict.

Findings

The results suggest that in the presence of second order information on social trust, third order information doesn't have an effect on cooperation.

Originality

The study extends the theory of third order inference to understanding the role of social trust at the first, second, and third levels in public goods dilemmas. It puts second order information in competition with third order in predicting cooperation. It suggests that resolving the uncertainty over the second order beliefs of a collective is key to preventing inefficient equilibriums when second and third order beliefs conflict.

Details

Advances in Group Processes
Type: Book
ISBN: 978-1-83797-477-1

Keywords

Article
Publication date: 10 February 2023

Jin Zhang, Xinmai Li, Banggang Wu, Liying Zhou and Xiang Chen

A critical step in influencer marketing is influencer outreach, where a brand reaches out to an influencer and forms a partnership. Yet little is known about how factors related…

Abstract

Purpose

A critical step in influencer marketing is influencer outreach, where a brand reaches out to an influencer and forms a partnership. Yet little is known about how factors related to this process might influence the outcomes of sponsored posts. To address this gap, the authors investigated whether, how and when the order of influencers' product use and brand outreach (i.e. use/outreach order) affects post persuasiveness.

Design/methodology/approach

The authors conducted three experimental studies. Studies 1 and 2 examined the effect of disclosure type (use-first, outreach-later vs. outreach-first, use-later vs. no disclosure) on consumers' responses to the post. Study 3 investigated the moderating effects of compensation disclosure type.

Findings

The results revealed that when the influencer used the product before (vs. after) being contacted by the brand, consumers had more favorable attitudes about the product and greater purchase intention upon reading the sponsored posts; perceived information diagnosticity mediated this effect. However, this tendency was mitigated if the influencer disclosed the specific monetary payment from the brand.

Originality/value

This research advances understanding of sponsorship disclosure and provides a way to manage its impact on message persuasiveness.

Details

Journal of Research in Interactive Marketing, vol. 17 no. 6
Type: Research Article
ISSN: 2040-7122

Keywords

Article
Publication date: 14 July 2023

Guozhi Xu, Xican Li and Hong Che

In order to improve the estimation accuracy of soil organic matter, this paper aims to establish a modified model for hyperspectral estimation of soil organic matter content based…

Abstract

Purpose

In order to improve the estimation accuracy of soil organic matter, this paper aims to establish a modified model for hyperspectral estimation of soil organic matter content based on the positive and inverse grey relational degrees.

Design/methodology/approach

Based on 82 soil sample data collected in Daiyue District, Tai'an City, Shandong Province, firstly, the spectral data of soil samples are transformed by the first order differential and logarithmic reciprocal first order differential and so on, the correlation coefficients between the transformed spectral data and soil organic matter content are calculated, and the estimation factors are selected according to the principle of maximum correlation. Secondly, the positive and inverse grey relational degree model is used to identify the samples to be identified, and the initial estimated values of the organic matter content are obtained. Finally, based on the difference information between the samples to be identified and their corresponding known patterns, a modified model for the initial estimation of soil organic matter content is established, and the estimation accuracy of the model is evaluated using the mean relative error and the determination coefficient.

Findings

The results show that the methods of logarithmic reciprocal first order differential and the first-order differential of the square root for transforming the original spectral data are more effective, which could significantly improve the correlation between soil organic matter content and spectral data. The modified model for hyperspectral estimation of soil organic matter has high estimation accuracy, the average relative error (MRE) of 11 test samples is 4.091%, and the determination coefficient (R2) is 0.936. The estimation precision is higher than that of linear regression model, BP neural network and support vector machine model. The application examples show that the modified model for hyperspectral estimation of soil organic matter content based on positive and inverse grey relational degree proposed in this article is feasible and effective.

Social implications

The model in this paper has clear mathematical and physics meaning, simple calculation and easy programming. The model not only fully excavates and utilizes the internal information of known pattern samples with “insufficient and incomplete information”, but also effectively overcomes the randomness and grey uncertainty in the spectral estimation of soil organic matter. The research results not only enrich the grey system theory and methods, but also provide a new approach for hyperspectral estimation of soil properties such as soil organic matter content, water content and so on.

Originality/value

The paper succeeds in realizing both a modified model for hyperspectral estimation of soil organic matter based on the positive and inverse grey relational degrees and effectively dealing with the randomness and grey uncertainty in spectral estimation.

Details

Grey Systems: Theory and Application, vol. 13 no. 4
Type: Research Article
ISSN: 2043-9377

Keywords

Article
Publication date: 11 January 2024

Marco Fabio Benaglia, Mei-Hui Chen, Shih-Hao Lu, Kune-Muh Tsai and Shih-Han Hung

This research investigates how to optimize storage location assignment to decrease the order picking time and the waiting time of orders in the staging area of low-temperature…

124

Abstract

Purpose

This research investigates how to optimize storage location assignment to decrease the order picking time and the waiting time of orders in the staging area of low-temperature logistics centers, with the goal of reducing food loss caused by temperature abuse.

Design/methodology/approach

The authors applied ABC clustering to the products in a simulated database of historical orders modeled after the actual order pattern of a large cold logistics company; then, the authors mined the association rules and calculated the sales volume correlation indices of the ordered products. Finally, the authors generated three different simulated order databases to compare order picking time and waiting time of orders in the staging area under eight different storage location assignment strategies.

Findings

All the eight proposed storage location assignment strategies significantly improve the order picking time (by up to 8%) and the waiting time of orders in the staging area (by up to 22%) compared with random placement.

Research limitations/implications

The results of this research are based on a case study and simulated data, which implies that, if the best performing strategies are applied to different environments, the extent of the improvements may vary. Additionally, the authors only considered specific settings in terms of order picker routing, zoning and batching: other settings may lead to different results.

Practical implications

A storage location assignment strategy that adopts dispersion and takes into consideration ABC clustering and shipping frequency provides the best performance in minimizing order picker's travel distance, order picking time, and waiting time of orders in the staging area. Other strategies may be a better fit if the company's objectives differ.

Originality/value

Previous research on optimal storage location assignment rarely considered item association rules based on sales volume correlation. This study combines such rules with several storage planning strategies, ABC clustering, and two warehouse layouts; then, it evaluates their performance compared to the random placement, to find which one minimizes the order picking time and the order waiting time in the staging area, with a 30-min time limit to preserve the integrity of the cold chain. Order picking under these conditions was rarely studied before, because they may be irrelevant when dealing with temperature-insensitive items but become critical in cold warehouses to prevent temperature abuse.

Details

The International Journal of Logistics Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0957-4093

Keywords

Article
Publication date: 27 February 2024

Manuel Brauch, Matin Mohaghegh and Andreas Größler

One pertinent dynamic phenomenon in supply chains is the amplification of order variance, i.e. the bullwhip effect. Its continued significance is underscored in contemporary…

Abstract

Purpose

One pertinent dynamic phenomenon in supply chains is the amplification of order variance, i.e. the bullwhip effect. Its continued significance is underscored in contemporary empirical research. While numerous publications have pinpointed various causes of the bullwhip effect, there remains a gap in their systematic consolidation. The purpose of this paper is to compile a comprehensive list of the causes of the bullwhip effect from existing literature and categorize them appropriately.

Design/methodology/approach

This study conducts a systematic literature review to offer a comprehensive overview of bullwhip effect causes addressed in the existing literature. The identified causes are categorized using a qualitative content analysis approach.

Findings

The study shows the diversity of the causes of the bullwhip effect and their interdependencies. In addition, this study demonstrates that, at the highest level of aggregation, causes of the bullwhip effect can be classified into four main categories: causes inherent in the system structure, causes related to uncertainty, causes related to misaligned incentives and causes related to inadequate cognition of the situation.

Originality/value

The work provides an extensive overview and categorization of bullwhip effect causes, offering valuable insights for both researchers and practitioners seeking a deeper understanding of this phenomenon. In addition, it underscores managerial implications and highlights future research opportunities.

Details

Management Research Review, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2040-8269

Keywords

Article
Publication date: 3 October 2022

Colleen Carraher Wolverton, Tracey Rizzuto, Jason B. Thatcher and Wynne Chin

An organization’s competitive advantage can be strengthened if they are able to identify highly creative individuals. In fact, organizational success in the 21st century may…

Abstract

Purpose

An organization’s competitive advantage can be strengthened if they are able to identify highly creative individuals. In fact, organizational success in the 21st century may depend upon a firm’s ability to identify highly creative individuals who are able to develop novel and useful ideas, which are the outcome of creativity. The authors posit that Information Technology (IT) plays a significant role in creativity.

Design/methodology/approach

Applying the componential view of creativity, the authors propose the theoretically-derived concept of Individual IT Creativity (IITC). Utilizing a 5-phase methodology, the authors provide a theoretically-derived and rigorously-validated measure of IITC.

Findings

This study demonstrates that IITC is manifested in individuals who (1) possess IT expertise; (2) are motivated by IT tasks and (3) exhibit IT creativity-relevant processes. The authors then develop a scale to measure IITC and examine IITC within a broader nomological network.

Originality/value

This study facilitates the investigation of new streams of research into IITC, including new possible outcomes in addition to IT acceptance.

Details

Information Technology & People, vol. 36 no. 6
Type: Research Article
ISSN: 0959-3845

Keywords

Article
Publication date: 23 September 2022

Mehdi Hassanzadeh, Mohammad Taheri, Sajjad Shokouhyar and Sina Shokoohyar

This study examines opinion leadership's personal and social characteristics to see which one is more effective in opinion leadership in four different industries: fashion, travel…

Abstract

Purpose

This study examines opinion leadership's personal and social characteristics to see which one is more effective in opinion leadership in four different industries: fashion, travel and tourism, wellness and book and literature. The specific subject of this investigation is how largely openness, exhibitionism and competence in interpersonal relationships and status and attitude homophily affect the opinion leadership and the decision-making of opinion leaders' followers.

Design/methodology/approach

The proposed model was tested with the questionnaire shared via stories featured on Instagram among followers of four micro-influencers in different industries. For the purpose of testing the offered hypotheses of this study, the partial least squares method was used.

Findings

The findings show that openness, exhibitionism and competence in interpersonal relationships have a substantial effect on opinion leadership. It was also evident that status and attitude homophily impact opinion leadership. The model supports the effect of both personal and social characteristics on opinion leadership; however, based on the results, the effect of personal characteristics on opinion leadership is more remarkable, both in a direct relationship and through the mediating role of para-social interaction.

Originality/value

This study is novel in categorizing opinion leaders' attributes in two different extents of personal and social characteristics. The authors defined a model of the effectiveness of each personal and social characteristic on opinion leaders. The model investigates whether the personal or social characteristics have the most effect on opinion leadership, particularly with the mediating role of para-social interaction.

Details

Aslib Journal of Information Management, vol. 75 no. 6
Type: Research Article
ISSN: 2050-3806

Keywords

Article
Publication date: 8 June 2023

Jiahao Liu, Tao Gu and Zhixue Liao

The purpose of this paper is to consider three factors, namely, intra-week demand fluctuations, interrelationship between the number of robots and order scheduling and conflicting…

Abstract

Purpose

The purpose of this paper is to consider three factors, namely, intra-week demand fluctuations, interrelationship between the number of robots and order scheduling and conflicting objectives (i.e. cost minimization and customer satisfaction maximization), to optimize the robot logistics system.

Design/methodology/approach

The number of robots and the sequence of delivery orders are first optimized using the heuristic algorithm NSGACoDEM, which is designed using genetic algorithm and composite difference evolution. The superiority of this method is then confirmed by a case study of a four-star grade hotel in South Korea and several comparative experiments.

Findings

Two performance metrics reveal the superior performance of the proposed approach compared to other baseline approaches. Results of comparative experiments found that the consideration of three influencing factors in the operation design of a robot logistic system can effectively balance cost and customer satisfaction over the course of a week in hotel operation and optimize robot scheduling flexibility.

Practical implications

The results of this study reveal that numerous factors (e.g. intra-week demand fluctuations) can optimize the performance efficiency of robots. The proposed algorithm can be used by hotels to overcome the influence of intra-week demand fluctuations on robot scheduling flexibility effectively and thereby enhance work efficiency.

Originality/value

The design of a novel algorithm in this study entails enhancing the current robot logistics system. This algorithm can successfully manage cost and customer satisfaction during off-seasons and peak seasons in the hotel industry while offering diversified schemes to various types of hotels.

Details

International Journal of Contemporary Hospitality Management, vol. 36 no. 1
Type: Research Article
ISSN: 0959-6119

Keywords

Article
Publication date: 15 February 2022

Simplice Asongu, Christelle Meniago and Raufhon Salahodjaev

This study investigates (1) the effect of foreign direct investment (FDI) on total factor productivity (TFP) and economic growth dynamics and (2) the relevance of value added from…

Abstract

Purpose

This study investigates (1) the effect of foreign direct investment (FDI) on total factor productivity (TFP) and economic growth dynamics and (2) the relevance of value added from three economic sectors in modulating the established effect of FDI on TFP and economic growth dynamics.

Design/methodology/approach

The geographical and temporal scopes are respectively 25 Sub-Saharan African countries and the period 1980–2014. The empirical evidence is based on non-interactive and interactive generalised method of moments.

Findings

The following main findings are established. First, FDI has a positive effect on gross domestic product (GDP) growth, GDP per capita and welfare real TFP. Second, the effect of FDI is negative on real GDP and TFP while the impact is insignificant on real TFP growth and welfare TFP. Third, values added to the three economic sectors largely modulate FDI to produce negative net effects on TFP and growth dynamics.

Practical implications

Policy implications are discussed with particular emphasis on the need to complement added value across various economic sectors in order to leverage on the benefits of FDI in TFP and economic growth.

Originality/value

To the best of the authors’ knowledge, this is the first study to assess how value added from various economic sectors affect the relevance of FDI on macroeconomic outcomes.

Details

International Journal of Emerging Markets, vol. 18 no. 11
Type: Research Article
ISSN: 1746-8809

Keywords

Article
Publication date: 15 May 2023

Ehsan Kordi, Mohammadreza Abdoli and Hassan Valiyan

With the emergence of the basis of intellectual capital, competitive advantage was considered as the focus of competitive strategies, and the knowledge resulting from this…

Abstract

Purpose

With the emergence of the basis of intellectual capital, competitive advantage was considered as the focus of competitive strategies, and the knowledge resulting from this approach became the basis for the development and strategic directions of companies in various fields of the company such as finance and accounting. The purpose of this study is sustainable intellectual capital reporting framework and evaluation of key examples in the context of capital market companies.

Design/methodology/approach

The methodology of this study was exploratory from the point of view of the developmental result and based on the type of objective and qualitative and quantitative basis was used to collect the data. The statistical population in the qualitative part was university experts and in the quantitative part financial managers of capital market companies. Data collection tools were interviews in the qualitative part and fuzzy scales and language comparison checklists in the quantitative part. Therefore, first through three stages of coding, the dimensions of the model were identified, and based on the fuzzy Delphi analysis, the reliability level was determined through the average between the first round and the second round of Delphi. Finally, through the default tests, the appropriate fuzzy model was first determined, and then hierarchical fuzzy analysis based on TODIM's approach was used to determine the most favorable axis of sustainable intellectual capital reporting.

Findings

The results in the qualitative part indicate the existence of 3 categories and 6 components and 39 conceptual themes in the form of a six-dimensional model. In the quantitative part, the results showed that by confirming the dimensions identified through fuzzy Delphi analysis, the most desirable axis of intellectual capital reporting is the component of technological capital reporting, which can play a more effective role in sustainable reporting.

Originality/value

This study, relying on the importance of the consequences of sustainable intellectual capital reporting, tries to evaluate the consequences of this field of financial reporting due to the lack of a coherent theoretical framework about capital market companies. In addition, the framework presented in this study promotes integrated thinking for firms to it would provide some level of incentive to those charged with governance concerning the voluntary compliance with the sustainable intellectual capital reporting framework.

Details

Journal of Advances in Management Research, vol. 20 no. 4
Type: Research Article
ISSN: 0972-7981

Keywords

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