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1 – 10 of over 1000
Open Access
Article
Publication date: 29 September 2020

Babajide Oyewo, Oluwafunmilayo Ajibola and Mohammed Ajape

This study investigates the characteristics of business and management consulting firms (firm size, international affiliation and scope of operation) affecting the adoption rate…

3723

Abstract

Purpose

This study investigates the characteristics of business and management consulting firms (firm size, international affiliation and scope of operation) affecting the adoption rate (i.e. recency of adopting big data analytics (BDA) as a new idea) and usage level of BDA. Ten critical areas of BDA application to business and management consulting were investigated, (1) Human Resource Management; (2) Risk Management; (3) Financial Advisory Services; (4) Innovation and Strategy; (5) Brand Building and Product Positioning; (6) Market Research/Diagnostic Studies; (7) Scenario-Based Planning/Business Simulation; (8) Information Technology; (9) Internal Control/Internal Audit; and (10) Taxation and Tax Management.

Design/methodology/approach

Survey data was obtained through a structured questionnaire from one hundred and eighteen (118) consultants in Nigeria from diverse consulting firm settings in terms of size, international affiliation and scope of operation (Big 4/non-Big 4 firms). Data was analyzed using descriptive statistics, cluster analysis, multivariate analysis of variance (MANOVA), multivariate discriminant analysis and multivariable logistic regression.

Findings

Whereas organizational characteristics such as firm size, international affiliation and scope of operation significantly determine the adoption rate of BDA, two attributes (international affiliation and scope of operation) significantly explain BDA usage level. Internationally affiliated consulting firms are more likely to record higher usage level of BDA than local firms. Also, the usage level of BDA by the Big 4 accounting/consulting firms is expected to be higher in comparison to non-Big 4 firms.

Practical implications

Contrary to common knowledge that firm size is positively associated with the adoption of an innovation, the study found no evidence to support this claim in respect of the diffusion of BDA. Overall, it appears that the scope of operation is the strongest organizational factor affecting the diffusion of BDA among consulting firms.

Originality/value

The study contributes to knowledge by exposing the factors promoting the uptake of BDA in a developing country. The originality of the current study stems from the consideration that it is the first, to the researchers' knowledge, to investigate the application of BDA by consulting firms in the Nigerian context. The study adds to literature on management accounting in the digital economy.

Details

Journal of Asian Business and Economic Studies, vol. 28 no. 4
Type: Research Article
ISSN: 2515-964X

Keywords

Open Access
Article
Publication date: 9 March 2021

Linda Hantrais

The relative success of East Asian countries in controlling the spread of COVID-19 at its onset was widely attributed to their capacity to learn from previous experience of…

Abstract

The relative success of East Asian countries in controlling the spread of COVID-19 at its onset was widely attributed to their capacity to learn from previous experience of epidemics, their preparedness to deal with new threats to health, and public acceptance of the need to comply unquestioningly with stringent measures to contain the virus. The conditions were very different when Europe was recognised as the epicentre of the pandemic in March 2020. In a climate of uncertainty, intensified by inconsistent scientific advice and intractable political dilemmas, European governments embarked on a steep learning curve. They experimented with packages of measures based on limited and often conflicting evidence about their effectiveness in preventing transmission of the disease and high excess death rates, amid growing concern about the collateral damage being caused to public health, and to social and economic life.

Drawing on a wide range of multi-disciplinary published materials and official statistics, research articles, reports, briefings and academic debates, as well as media headlines and commentary, this briefing assesses policy learning during the first wave of the pandemic in Europe and asks:

What lessons did European countries, individually and collectively, draw from their own experiences and from the policy responses of neighbouring countries when Europe was the epicentre of the COVID-19 pandemic?

Were decision-takers better prepared to contain further waves of the disease and to improve outcomes?

Details

Emerald Open Research, vol. 1 no. 13
Type: Research Article
ISSN: 2631-3952

Keywords

Open Access
Article
Publication date: 7 June 2022

Ana Gutiérrez, Jose Aguilar, Ana Ortega and Edwin Montoya

The authors propose the concept of “Autonomic Cycle for innovation processes,” which defines a set of tasks of data analysis, whose objective is to improve the innovation process…

1018

Abstract

Purpose

The authors propose the concept of “Autonomic Cycle for innovation processes,” which defines a set of tasks of data analysis, whose objective is to improve the innovation process in micro-, small and medium-sized enterprises (MSMEs).

Design/methodology/approach

The authors design autonomic cycles where each data analysis task interacts with each other and has different roles: some of them must observe the innovation process, others must analyze and interpret what happens in it, and finally, others make decisions in order to improve the innovation process.

Findings

In this article, the authors identify three innovation sub-processes which can be applied to autonomic cycles, which allow interoperating the actors of innovation processes (data, people, things and services). These autonomic cycles define an innovation problem, specify innovation requirements, and finally, evaluate the results of the innovation process, respectively. Finally, the authors instance/apply the autonomic cycle of data analysis tasks to determine the innovation problem in the textile industry.

Research limitations/implications

It is necessary to implement all autonomous cycles of data analysis tasks (ACODATs) in a real scenario to verify their functionalities. Also, it is important to determine the most important knowledge models required in the ACODAT for the definition of the innovation problem. Once determined this, it is necessary to define the relevant everything mining techniques required for their implementations, such as service and process mining tasks.

Practical implications

ACODAT for the definition of the innovation problem is essential in a process innovation because it allows the organization to identify opportunities for improvement.

Originality/value

The main contributions of this work are: For an innovation process is specified its ACODATs in order to manage it. A multidimensional data model for the management of an innovation process is defined, which stores the required information of the organization and of the context. The ACODAT for the definition of the innovation problem is detailed and instanced in the textile industry. The Artificial Intelligence (AI) techniques required for the ACODAT for the innovation problem definition are specified, in order to obtain the knowledge models (prediction and diagnosis) for the management of the innovation process for MSMEs of the textile industry.

Details

Applied Computing and Informatics, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2634-1964

Keywords

Open Access
Article
Publication date: 21 June 2021

Emong Herbert Robert

This study aims to develop an econometric analysis of how modern agriculture can be a fundamental instrument for reducing the levels of multidimensional poverty in Uganda. It…

Abstract

Purpose

This study aims to develop an econometric analysis of how modern agriculture can be a fundamental instrument for reducing the levels of multidimensional poverty in Uganda. It demonstrates the importance of agriculture in reducing inequalities amongst the poor while focusing on the relationship between increasing productions from modern agricultural practices and the poverty level across the country.

Design/methodology/approach

The study explores Box–Jenkins approach to cereal production data with the use of econometric analysis as the main tool to determine the implications of modern agricultural practices in Uganda. Most poor people around the world are in marginalized rural environments, and agriculture provides for their livelihoods. This makes agricultural development crucial for reducing multidimensional poverty on a large scale and needs development within agriculture to be enhanced. Education, health and standard of living are the three dimensions considered from the weighted indicators, amounting to 30%, to be categorized poor in the three dimensions.

Findings

Modernization of agriculture is an ultimate solution to multidimensional poverty reduction in Uganda through employment generation and the effects of food prices. Shreds of evidence support the theories that agricultural incomes together with the actual wages increase with a general rise in the rural non-agricultural economy. Results depict a close correlation between national income and GDP per capita which is a very significant indication that more application of agricultural technology would lead to a sub sequential improvement of livelihoods engaged in agricultural practices.

Originality/value

Agriculture remains a vital sector that employs a greater portion of the population in Uganda’s economy. Major roles have been played by the sector in the economy including employment opportunities, rural household incomes, food supplies and a reduction in poverty from a multidimensional front. Exploring the behavior of poverty level using modern agriculture as an indicator and its relationship with the poverty level arising from improved agricultural practices could provide a meaningful display of variation in poverty across the regions at the country level.

Details

Review of Economics and Political Science, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2356-9980

Keywords

Open Access
Article
Publication date: 28 December 2020

Bodo Steiner and Moritz Brandhoff

This paper aims to explore the role of configurations of relationship quality dimensions for explaining sources of behavioral outcomes in the globalized manufacturing industry.

4483

Abstract

Purpose

This paper aims to explore the role of configurations of relationship quality dimensions for explaining sources of behavioral outcomes in the globalized manufacturing industry.

Design/methodology/approach

A joint analysis of behavioral and objective performance data from globalized manufacturing links perceptual customer metrics that relate to dimensions of relationship quality (i.e. attitudinal loyalty, perceived customer orientation, customers’ perceived innovativeness of the supplier and perceived customer influence on supplier innovation) with behavioral outcomes (i.e. share of wallet (SOW) and customer account profitability). Using data from a global business-to-business (B2B) customer survey together with archival performance data from a multinational mechanical engineering firm, a fuzzy set qualitative comparative analysis (fsQCA) is performed.

Findings

The fsQCA results suggest that perceptual customer metrics related to innovation can be relevant aspects of relationship quality, in line with Anderson and Mittal’s (2000) satisfaction-repurchase-profitability chain framework and its adaptation to SOW. However, the underlying complexities in the different combinations of attributes in the recipe are such that they are not equifinal in leading to higher SOW or higher profitability. This paper finds indications for non-linearities between perceptual measures investigated and profitability of customer accounts, with particular relevance for the role of perceived customer orientation, perceived product innovativeness of the supplier and attitudinal loyalty.

Research limitations/implications

The analysis faces a number of limitations, starting with its reliance on cross-sectional survey data, which does not enable us to account for feedback mechanisms, for example, arising from customer perceptions regarding innovation aspects. The lack of a multidimensional conceptionalization of the perceptual customer constructs may have limited the analysis, considering also recent evidence from retail companies in the furniture sector in Spain, suggesting that the multidimensional conceptualization of relationship value explained satisfaction and loyalty levels to a greater extent than the one-dimensional conceptualization (Ruiz-Martínez et al., 2019).

Practical implications

In terms of managerial implication, the results suggest that customers perceive limited value in participating in the focal firm’s innovation value chain funnel, hence customer loyalty cannot be bought using simple incentive strategies. The results with regard to customer account profitability suggest that B2B customers investigated here may distinguish when interacting with their globalized supplier in the innovation funnel: they may see a positive customer value when the innovation is a product, and thus, relation-specific, whereas they may see limited customer value when innovation is considered in more generic terms (customers’ perceived influence on supplier innovation in general).

Originality/value

This paper starts from the premise that perceptual customer metrics can matter for supplier performance, as the customer relationship and customer value management research has shown. However, there is limited empirical evidence from globalized manufacturing sectors incorporating perceptual constructs in behavioral outcomes, and limited evidence assessing customer-perceived value in such sectors through alternate approaches to main-effects focused analyzes. We employ qualitative comparative analysis using fuzzy sets (Russo et al., 2019) to address these gaps, focusing on two key behavioral outcomes, namely, customer account profitability and SOW.

Open Access
Article
Publication date: 17 August 2021

Cinzia Daraio, Gianpaolo Iazzolino, Domenico Laise, Ilda Maria Coniglio and Simone Di Leo

The purpose of this paper is to address the issue of knowledge visualization and its connection with performance measurement from an epistemological point of view, considering…

Abstract

Purpose

The purpose of this paper is to address the issue of knowledge visualization and its connection with performance measurement from an epistemological point of view, considering quantification and measurement not just as technical questions but showing their relevant implications on the management decision-making of knowledge-based organizations.

Design/methodology/approach

This study proposes a theoretical contribution that combines two lines of research for identifying the three main meta-choices problems that arise in the multidimensional benchmarking of knowledge-based organizations. The first is the meta-choice problem related to the choice of the algorithm used (Iazzolino et al., 2012; Laise et al., 2015; Daraio, 2017a). The second refers to the choice of the variables to be included in the model (Daraio, 2017a). The third concerns the choice of the data on which the analyses are carried out (Daraio, 2017a).

Findings

The authors show the interplay existing among the three meta-choices in multidimensional benchmarking, considering as key performance indicators intellectual capital, including Human Capital, Structural Capital and Relational Capital, and performances, evaluated in financial and non-financial terms. This study provides an empirical analysis on Italian Universities, comparing the ranking distributions obtained by several efficiency and multi-criteria methods.

Originality/value

This study demonstrates the difficulties of the “implementation problem” in performance measurement, related to the subjectivity of results of the evaluation process when there are many evaluation criteria, and proposes the adoption of the technologies of humility related to the awareness that we can only achieve “satisficing” results.

Details

Management Decision, vol. 60 no. 4
Type: Research Article
ISSN: 0025-1747

Keywords

Open Access
Article
Publication date: 21 October 2021

Elena Barbierato, Iacopo Bernetti and Irene Capecchi

Wine packaged tours as a specific aspect of wine tourism have so far been neglected in research, for this reason, the purpose of this study is to study the key elements for the…

3636

Abstract

Purpose

Wine packaged tours as a specific aspect of wine tourism have so far been neglected in research, for this reason, the purpose of this study is to study the key elements for the success of the wine tour in Tuscany (Italy), evaluating the points of strength and weakness.

Design/methodology/approach

The study combines approaches of text mining, sentiment analysis and natural language processing, drawing on data from the TripAdvisor platform, obtaining through an automatic procedure 9,616 reviews from 600 tours in the years 2010–2020.

Findings

The authors identified six elements of successful wine tours expressed by research subjects: tour guide; logistical aspects; the quality of the wine; the quality of the food; complementary tourist and recreational activities; the landscape and historic villages. The key strength associated with success was the integration of the leading wine product with food, landscape and historic villages, while the main criticisms were concerned with the organization and planning of the tour. Furthermore, the tour guide also plays a fundamental role in consumer satisfaction.

Research limitations/implications

The limitations of the method were linked to the origin of the data used. The main one is that TripAdvisor does not allow you to have social and personal information about the tourist who wrote the review; therefore, the methods are substantially complementary to the traditional survey through questionnaires.

Practical implications

The proposed model can be used both by professionals to improve the quality of their products and by policymakers to promote the territorial development of quality wine-growing areas.

Social implications

The proposed model can be useful for policymakers to promote the territorial development of quality wine-growing areas.

Originality/value

The methodology we tested is easily transferable to many countries and to the authors’ knowledge, for the first time attempts to combine multidimensional scaling, sentiment analysis and natural language processing approaches.

Details

International Journal of Wine Business Research, vol. 34 no. 2
Type: Research Article
ISSN: 1751-1062

Keywords

Open Access
Article
Publication date: 8 September 2023

Youssef Malhouni and Charif Mabrouki

The purpose of this study is to analyze the challenges encountered by international nongovernmental organizations (INGOs) operating in armed conflicts within the Democratic…

Abstract

Purpose

The purpose of this study is to analyze the challenges encountered by international nongovernmental organizations (INGOs) operating in armed conflicts within the Democratic Republic of the Congo (DRC) and the Central African Republic (CAR). Through a 20-month fieldwork analysis, this research maps logistical risks and highlights key obstacles on the ground for successful humanitarian deployments in dynamically changing and complex environments. The study brings together academics and practitioners, providing practical and concrete recommendations for nongovernmental organizations (NGOs) to focus on in the conflict zones studied.

Design/methodology/approach

Using a mixed-methods approach that combines qualitative and quantitative methods, this research provides valuable insights into the challenges faced by INGOs in conflict zones. After collecting data from the field, including interviews with key stakeholders and on-the-ground observations, the data analysis uses software tools such as Text Analysis Markup System analyzer and Macbeth. By adhering to ethical principles and incorporating a reflexive analysis, the study sheds light on the multidimensional nature of successful humanitarian deployments.

Findings

The primary risk in all armed conflict zones, including the DRC and CAR, is insecurity. However, to achieve a successful humanitarian deployment in such contexts, a multidimensional approach is required. This involves first securing the acceptance of local communities and conflict parties, which can be achieved through a deep understanding of both political and customary structures, with a focus on respecting key engagement leaders. Sustainability also plays a crucial role, and NGOs must maintain a secure stock of energy and provide greater initiative for on-the-ground managers to meet the expressed needs of beneficiary populations and involve them from the planning stage onwards. Finally, effective communication, cooperation and collaboration with United Nations Office for the Coordination of Humanitarian Affairs are essential to overcome procurement, technical and security risks, particularly during the initial deployment phases.

Originality/value

This study provides an illustration of the uncommon practice of conducting collaborative research in humanitarian settings amidst two neighboring areas of armed conflict. The authors identified 268 common risk factors across eight categories during five deployment phases. To analyze these risks based on criticality and NGO responsiveness, the authors used a multicriteria method. This approach allowed the authors to validate unanimous judgments, resulting in valuable insights and concrete recommendations.

Details

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

Keywords

Open Access
Article
Publication date: 19 January 2024

Ozge Kozal, Mehmet Karacuka and Justus Haucap

In this study the authors aim to comprehensively investigate the determinants of voting behavior in Turkey, with a specific focus on the dynamics of the center-periphery debate…

Abstract

Purpose

In this study the authors aim to comprehensively investigate the determinants of voting behavior in Turkey, with a specific focus on the dynamics of the center-periphery debate. Mainly, the authors focus on regional voting patterns during the period that is dominated by the Justice and Development Party (JDP/AKP) in the elections. The authors apply the random effects generalized least squares (GLS) methodology, and analyze electoral data covering four pivotal parliamentary elections (2007, 2011, 2015 and 2018) across all 81 provinces (NUTS III regions). The authors individually examine voting dynamics of the four major parties in parliament: the JDP/AKP, the Republican People's Party (RPP/CHP), the Nationalist Movement Party (NMP/MHP) and the Peoples' Democratic Party (PDP/HDP). The authors contribute to a comprehensive understanding of how socioeconomic cleavages, economic performance, party alignment and social dynamics shape voter preferences in the Turkish context, thereby addressing gaps in the existing literature.

Design/methodology/approach

This research employs an ecological study of Turkish NUTS III sub-regions, covering national elections from 2007 to 2018. The authors utilize the random effects GLS method to account for heteroscedasticity and time effects. The inclusion of the June and November 2015 elections enables a comprehensive analysis of the evolving dynamics in Turkish voting behavior. The results remain robust when applying pooled OLS and fixed effect OLS techniques for control.

Findings

The study's findings reveal that economic performance, specifically economic growth, plays a pivotal role in the sustained dominance of the JDP/AKP party. Voters closely associate JDP preference with economic growth, resulting in higher voting shares during periods of economic prosperity. Along with economic growth; share of agriculture in regions' GDP, female illiteracy rate, old population rate, net domestic migration, terrorism and party alignment are also influential factors in the Turkish case. Furthermore, differences among sociocultural groups, and East–West dichotomy seem to be important factors that reveal the impact of social cleavages to understand electoral choice in Turkey.

Originality/value

This study contributes to the existing literature by offering a comprehensive multidimensional analysis of electoral behavior in Turkey, focusing on the JDP/AKP dominance period. The main contribution of this study is its multidimensional perspective on the power bases of all main parties, considering key voter choice theories (cleavages, party alignment and retrospective economic performance voting) that have not been systematically analyzed in prior research. The main research question of this study is to examine which factors affect voting behavior in Turkey and how the dynamics of center-periphery or eastern-western region voting behavior under the JDP hegemony can be explained. The contribution of this study consists not only in its empirical testing of panel data approaches but also in its comprehensive analysis of four major political parties. Building upon existing studies in the literature, this research seeks to extend the understanding of voting dynamics for the four main parties in the parliament — JDP/AKP, RPP/CHP, NMP/MHP and PPDP/HDP — by delving into their dynamics individually, thereby expanding the scope of previous studies. This study aims to make a contribution by not only empirically testing panel data approaches but also conducting a comprehensive analysis of four major political parties. Furthermore, the separate inclusion of the 2015 elections and utilization of a panel data approach enrich the analysis by capturing the evolving dynamics of Turkish voting behavior. The study underscores the significance of socioeconomic factors, economic performance and social cleavages for voters' choices within the context of a dominant party rule.

Details

Review of Economics and Political Science, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2356-9980

Keywords

Open Access
Article
Publication date: 28 July 2020

Noura AlNuaimi, Mohammad Mehedy Masud, Mohamed Adel Serhani and Nazar Zaki

Organizations in many domains generate a considerable amount of heterogeneous data every day. Such data can be processed to enhance these organizations’ decisions in real time…

3505

Abstract

Organizations in many domains generate a considerable amount of heterogeneous data every day. Such data can be processed to enhance these organizations’ decisions in real time. However, storing and processing large and varied datasets (known as big data) is challenging to do in real time. In machine learning, streaming feature selection has always been considered a superior technique for selecting the relevant subset features from highly dimensional data and thus reducing learning complexity. In the relevant literature, streaming feature selection refers to the features that arrive consecutively over time; despite a lack of exact figure on the number of features, numbers of instances are well-established. Many scholars in the field have proposed streaming-feature-selection algorithms in attempts to find the proper solution to this problem. This paper presents an exhaustive and methodological introduction of these techniques. This study provides a review of the traditional feature-selection algorithms and then scrutinizes the current algorithms that use streaming feature selection to determine their strengths and weaknesses. The survey also sheds light on the ongoing challenges in big-data research.

Details

Applied Computing and Informatics, vol. 18 no. 1/2
Type: Research Article
ISSN: 2634-1964

Keywords

1 – 10 of over 1000