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Book part
Publication date: 16 November 2023

Jaekyung Ha, Stine Grodal and Ezra W. Zuckerman Sivan

Our prior work has identified a trade-off that new entrants face in obtaining favorable market reception, whereby initial entrants suffer from a deficit of legitimacy whereas…

Abstract

Our prior work has identified a trade-off that new entrants face in obtaining favorable market reception, whereby initial entrants suffer from a deficit of legitimacy whereas later entrants suffer from a deficit of authenticity. This research has also proposed that a single mechanism is responsible for this trade-off: the tendency for customers and other stakeholders to assess the entrant's claim to originality based on the visible work that it has done to legitimate the new product or organizational form. This chapter extends and deepens our understanding of such “legitimation work” by showing how it can illuminate cases that seem in the first instance to defy this trade-off. In particular, we focus on two “off-diagonal” cases: (a) when, as in the case of “patent trolls” and fraudulent innovators, early entrants are viewed as inauthentic despite having a credible claim to originality; (b) when late entrants, as in the case of Dell Computers, mechanical watches and baseball ballparks, are viewed as authentic despite obviously not being the originators. We clarify how each off-diagonal case represents an ‘exception that proves the rule’ whereby audiences attribute authenticity on the basis of legitimation work rather than on the order of entry per se. The last case also leads to an opportunity to clarify why “cultural appropriation” can sometimes project authenticity and sometimes inauthenticity, why audiences bother to make inferences about a producer's authenticity on the basis of visible legitimation work, and why legitimacy is a universal goal of early movers whereas authenticity varies in its importance.

Details

Organization Theory Meets Strategy
Type: Book
ISBN: 978-1-83753-869-0

Keywords

Article
Publication date: 3 April 2023

Kangkang Yu, Jack Cadeaux, Ben Nanfeng Luo and Cheng Qian

This study aims to extend ambidexterity theory from the perspective of organisational learning and examine how process ambidexterity, which comprises operational flexibility and…

Abstract

Purpose

This study aims to extend ambidexterity theory from the perspective of organisational learning and examine how process ambidexterity, which comprises operational flexibility and operational routine, responds to environmental uncertainty and ultimately reduces organisational risks.

Design/methodology/approach

This study tests the hypotheses by analysing 464 annual reports of 115 listed companies in the Chinese agricultural and food industry using content and secondary data analyses. Four case studies are also provided.

Findings

The results show that (1) environmental uncertainty has a positive effect on either operational flexibility or operational routine; (2) both operational flexibility and operational routine have negative effects on organisational risks, supporting the view that process ambidexterity mediates the relationship between environmental uncertainty and organisational risks; and (3) organisational slack plays the role of “double-edged sword” by negatively moderating the effect of environmental uncertainty on operational flexibility and positively moderating the effect of environmental uncertainty on operational routine.

Originality/value

In an uncertain environment, companies are exposed to greater risk. This study contributes to risk management in three ways: first, it extends ambidexterity theory to process management and proposes how process ambidexterity balances operational flexibility and routines. Second, it distinguishes between the different conditions under which flexibility or routines are superior. Third, it explains the mechanisms related to how organisations can resolve environmental uncertainty into risk through process ambidexterity.

Details

International Journal of Operations & Production Management, vol. 43 no. 12
Type: Research Article
ISSN: 0144-3577

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Article
Publication date: 12 October 2023

Xiaoli Su, Lijun Zeng, Bo Shao and Binlong Lin

The production planning problem with fine-grained information has hardly been considered in practice. The purpose of this study is to investigate the data-driven production…

Abstract

Purpose

The production planning problem with fine-grained information has hardly been considered in practice. The purpose of this study is to investigate the data-driven production planning problem when a manufacturer can observe historical demand data with high-dimensional mixed-frequency features, which provides fine-grained information.

Design/methodology/approach

In this study, a two-step data-driven optimization model is proposed to examine production planning with the exploitation of mixed-frequency demand data is proposed. First, an Unrestricted MIxed DAta Sampling approach is proposed, which imposes Group LASSO Penalty (GP-U-MIDAS). The use of high frequency of massive demand information is analytically justified to significantly improve the predictive ability without sacrificing goodness-of-fit. Then, integrated with the GP-U-MIDAS approach, the authors develop a multiperiod production planning model with a rolling cycle. The performance is evaluated by forecasting outcomes, production planning decisions, service levels and total cost.

Findings

Numerical results show that the key variables influencing market demand can be completely recognized through the GP-U-MIDAS approach; in particular, the selected accuracy of crucial features exceeds 92%. Furthermore, the proposed approach performs well regarding both in-sample fitting and out-of-sample forecasting throughout most of the horizons. Taking the total cost and service level obtained under the actual demand as the benchmark, the mean values of both the service level and total cost differences are reduced. The mean deviations of the service level and total cost are reduced to less than 2.4%. This indicates that when faced with fluctuating demand, the manufacturer can adopt the proposed model to effectively manage total costs and experience an enhanced service level.

Originality/value

Compared with previous studies, the authors develop a two-step data-driven optimization model by directly incorporating a potentially large number of features; the model can help manufacturers effectively identify the key features of market demand, improve the accuracy of demand estimations and make informed production decisions. Moreover, demand forecasting and optimal production decisions behave robustly with shifting demand and different cost structures, which can provide manufacturers an excellent method for solving production planning problems under demand uncertainty.

Details

Kybernetes, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0368-492X

Keywords

Article
Publication date: 13 February 2024

Jia Jin, Yi He, Chenchen Lin and Liuting Diao

Social recommendation has been recognized as a kind of e-commerce with large potential, but how social recommendations influence consumer decisions is still unclear. This paper…

Abstract

Purpose

Social recommendation has been recognized as a kind of e-commerce with large potential, but how social recommendations influence consumer decisions is still unclear. This paper aims to investigate how recommendations from different social ties influence consumers’ purchase intentions through both behavior and brain activity.

Design/methodology/approach

Utilizing behavioral (N = 70) and electroencephalogram (EEG) (N = 49) experiments, this study explored participants’ behavior and brain responses after being recommended by different social ties. The data were analyzed using statistical inference and event-related potential (ERP) analysis.

Findings

Behavioral results show that social tie strength positively impacts purchase intention, which can be fitted by a logarithmic model. Moreover, recommender-to-customer similarity and product affect mediate the effect of tie strength on purchase intention serially. EEG findings show that recommendations from weak tie strength elicit larger N100, N200 and P300 amplitudes than those from strong tie strength. These results imply that weak tie strength may motivate individuals to recruit more mental resources in social recommendation, including unconscious processing of consumer attention and conscious processing of cognitive conflict and negative emotion.

Originality/value

This study considers the effects of continuous social ties on purchase intention and models them mathematically, exploring the intrinsic mechanisms by which strong and weak ties influence purchase intentions through recommender-to-customer similarity and product affect, contributing to the applications of the stimulus-organism-response (SOR) model in the field of social recommendation. Furthermore, our study adopting EEG techniques bridges the gap of relying solely on self-report by providing an avenue to obtain relatively objective findings about the consumers’ early-occurred (unconscious) attentional responses and late-occurred (conscious) cognitive and emotional responses in purchase decisions.

Details

Internet Research, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1066-2243

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Article
Publication date: 22 December 2023

Vaclav Snasel, Tran Khanh Dang, Josef Kueng and Lingping Kong

This paper aims to review in-memory computing (IMC) for machine learning (ML) applications from history, architectures and options aspects. In this review, the authors investigate…

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Abstract

Purpose

This paper aims to review in-memory computing (IMC) for machine learning (ML) applications from history, architectures and options aspects. In this review, the authors investigate different architectural aspects and collect and provide our comparative evaluations.

Design/methodology/approach

Collecting over 40 IMC papers related to hardware design and optimization techniques of recent years, then classify them into three optimization option categories: optimization through graphic processing unit (GPU), optimization through reduced precision and optimization through hardware accelerator. Then, the authors brief those techniques in aspects such as what kind of data set it applied, how it is designed and what is the contribution of this design.

Findings

ML algorithms are potent tools accommodated on IMC architecture. Although general-purpose hardware (central processing units and GPUs) can supply explicit solutions, their energy efficiencies have limitations because of their excessive flexibility support. On the other hand, hardware accelerators (field programmable gate arrays and application-specific integrated circuits) win on the energy efficiency aspect, but individual accelerator often adapts exclusively to ax single ML approach (family). From a long hardware evolution perspective, hardware/software collaboration heterogeneity design from hybrid platforms is an option for the researcher.

Originality/value

IMC’s optimization enables high-speed processing, increases performance and analyzes massive volumes of data in real-time. This work reviews IMC and its evolution. Then, the authors categorize three optimization paths for the IMC architecture to improve performance metrics.

Details

International Journal of Web Information Systems, vol. 20 no. 1
Type: Research Article
ISSN: 1744-0084

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Article
Publication date: 20 February 2024

Xue-Yan Wu and Xujin Pu

Collaborative emission reduction among supply chain members has emerged as a new trend to achieve climate neutrality goals and meet consumers’ low-carbon preferences. However…

Abstract

Purpose

Collaborative emission reduction among supply chain members has emerged as a new trend to achieve climate neutrality goals and meet consumers’ low-carbon preferences. However, carbon information asymmetry and consumer mistrust represent significant obstacles. This paper investigates the value of blockchain technology (BCT) in solving the above issues.

Design/methodology/approach

A low-carbon supply chain consisting of one supplier and one manufacturer is examined. This study discusses three scenarios: non-adoption BCT, adoption BCT without sharing the supplier’s carbon emission reduction (CER) information and adoption BCT with sharing the supplier’s CER information. We analyze the optimal decisions of the supplier and the manufacturer through the Stackelberg game, identify the conditions in which the supplier and manufacturer adopt BCT and share information from the perspectives of economic and environmental performance.

Findings

The results show that adopting BCT benefits supply chain members, even if they do not share CER information through BCT. Furthermore, when the supplier’s CER efficiency is low, the manufacturer prefers that the supplier share this information. Counterintuitively, the supplier will only share CER information through BCT when the CER efficiencies of both the supplier and manufacturer are comparable. This diverges from the findings of existing studies, as the CER investments of the supplier and the manufacturer in this study are interdependent. In addition, despite the high energy consumption associated with BCT, the supplier and manufacturer embrace its adoption and share CER information for the sake of environmental benefits.

Practical implications

The firms in low-carbon supply chains can adopt BCT to improve consumers’ trust. Furthermore, if the CER efficiencies of the firms are low, they should share CER information through BCT. Nonetheless, a lower unit usage cost of BCT is the precondition.

Originality/value

This paper makes the first move to discuss BCT adoption and BCT-supported information sharing for collaborative emission reduction in supply chains while considering the transparency and high consumption of BCT.

Details

Kybernetes, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0368-492X

Keywords

Article
Publication date: 3 March 2023

Shirin Hassanzadeh Darani, Payam Rabbanifar, Mahmood Hosseini Aliabadi and Hamid Radmanesh

The purpose of this paper is to present a new system frequency response model with participation of wind-hydro-thermal units to overcome frequency deviations.

Abstract

Purpose

The purpose of this paper is to present a new system frequency response model with participation of wind-hydro-thermal units to overcome frequency deviations.

Design/methodology/approach

The extracted minimum frequency equation is considered as a constraint in security-constrained unit commitment calculations. Because of high-order polynomials in the frequency transfer function and high degree of nonlinearity of minimum frequency constraint, Routh stability criterion method and piecewise linearization technique are used to reduce system order and linearize the system frequency response model, respectively.

Findings

The results of this paper indicate that by using this model, the hourly minimum frequency is improved and is kept within defined range.

Originality/value

This combined model can be used to evaluate the frequency of the power system following unexpected load increase or generation disturbances. It also can be used to investigate the system frequency performance and ensure power system security which are caused by peak load or loss of generation in presence of renewable energies.

Details

COMPEL - The international journal for computation and mathematics in electrical and electronic engineering , vol. 42 no. 6
Type: Research Article
ISSN: 0332-1649

Keywords

Article
Publication date: 14 August 2023

Usman Tariq, Ranjit Joy, Sung-Heng Wu, Muhammad Arif Mahmood, Asad Waqar Malik and Frank Liou

This study aims to discuss the state-of-the-art digital factory (DF) development combining digital twins (DTs), sensing devices, laser additive manufacturing (LAM) and subtractive…

Abstract

Purpose

This study aims to discuss the state-of-the-art digital factory (DF) development combining digital twins (DTs), sensing devices, laser additive manufacturing (LAM) and subtractive manufacturing (SM) processes. The current shortcomings and outlook of the DF also have been highlighted. A DF is a state-of-the-art manufacturing facility that uses innovative technologies, including automation, artificial intelligence (AI), the Internet of Things, additive manufacturing (AM), SM, hybrid manufacturing (HM), sensors for real-time feedback and control, and a DT, to streamline and improve manufacturing operations.

Design/methodology/approach

This study presents a novel perspective on DF development using laser-based AM, SM, sensors and DTs. Recent developments in laser-based AM, SM, sensors and DTs have been compiled. This study has been developed using systematic reviews and meta-analyses (PRISMA) guidelines, discussing literature on the DTs for laser-based AM, particularly laser powder bed fusion and direct energy deposition, in-situ monitoring and control equipment, SM and HM. The principal goal of this study is to highlight the aspects of DF and its development using existing techniques.

Findings

A comprehensive literature review finds a substantial lack of complete techniques that incorporate cyber-physical systems, advanced data analytics, AI, standardized interoperability, human–machine cooperation and scalable adaptability. The suggested DF effectively fills this void by integrating cyber-physical system components, including DT, AM, SM and sensors into the manufacturing process. Using sophisticated data analytics and AI algorithms, the DF facilitates real-time data analysis, predictive maintenance, quality control and optimal resource allocation. In addition, the suggested DF ensures interoperability between diverse devices and systems by emphasizing standardized communication protocols and interfaces. The modular and adaptable architecture of the DF enables scalability and adaptation, allowing for rapid reaction to market conditions.

Originality/value

Based on the need of DF, this review presents a comprehensive approach to DF development using DTs, sensing devices, LAM and SM processes and provides current progress in this domain.

Open Access
Article
Publication date: 10 July 2023

Moses Muhwezi, Henry Mutebi, Samuel Ssekajja Mayanja, Benjamin Tukamuhabwa, Sheila Namagembe and Robert Kalema

Procuring relief products and services is a challenging process for humanitarian organizations (HOs), yet it accounts for approximately 65% of relief operations’ costs (Moshtari…

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Abstract

Purpose

Procuring relief products and services is a challenging process for humanitarian organizations (HOs), yet it accounts for approximately 65% of relief operations’ costs (Moshtari et al., 2021). This paper aims to examine how procurement internal controls, materials and purchasing procedure standardization influence information integration and procurement performance.

Design/methodology/approach

In this study, partial least square structural equation models and multigroup analysis were used to analyze data collected from 170 HOs.

Findings

Procurement internal controls and material and purchasing procedure standardization fully mediate between information integration and procurement performance.

Research limitations/implications

The study focuses only on HOs. Since humanitarian procurement projects take place over a period of several years, it is difficult to capture the long-term effects of information integration, procurement internal controls, material and purchasing procedure standardization and procurement performance. In this regard, a longitudinal study could be undertaken, provided that the required resources are available.

Practical implications

Procurement managers should implement information integration practices within acceptable procurement internal controls and standardize material and purchasing procedures to boost procurement performance.

Originality/value

By integrating information through procurement internal controls and standardizing material and purchasing procedures, procurement performance in a humanitarian setting can be systematically optimized.

Details

Journal of Humanitarian Logistics and Supply Chain Management, vol. 13 no. 4
Type: Research Article
ISSN: 2042-6747

Keywords

Article
Publication date: 6 June 2023

Moses Muhwezi, Henry Mutebi, Benjamin Tukamuhabwa, Samuel S. Mayanja, Isabella Izimba Kasiko and Rashid Balunywa

The purpose of this study is to empirically explore the influence of supply chain information integration (SCII) on supply chain innovativeness (SCI) and supply chain resilience…

Abstract

Purpose

The purpose of this study is to empirically explore the influence of supply chain information integration (SCII) on supply chain innovativeness (SCI) and supply chain resilience (SCRE).

Design/methodology/approach

Data from 403 manufacturing companies in Uganda were analyzed using Analysis of Moments of Structures version 27. Unmeasured common latent factors were used to minimize the bias of common methods.

Findings

SCII, SCI and SCRE have significant positive relationships. About 41% of SCII and SCRE are partially mediated by SCI.

Research limitations/implications

Considering variations in perception of SCRE, the cross-sectional nature of the study limits generalizability and transferability. Experiments and interviews are recommended to explore differences between firms in SCRE.

Practical implications

SCII and SCI capabilities buffer a firm’s SCRE.

Originality/value

This study establishes SCI as a mediator between SCII and SCRE by studying manufacturing firms in a developing country context.

Details

Continuity & Resilience Review, vol. 5 no. 3
Type: Research Article
ISSN: 2516-7502

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