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1 – 10 of 565Hsiao-Ting Tseng, Shizhen (Jasper) Jia, Tahir M. Nisar and Nick Hajli
The advantages of applying big data analytics for organizations to boost innovation performance are enormous. By collecting and analysing substantial amounts of data, firms can…
Abstract
Purpose
The advantages of applying big data analytics for organizations to boost innovation performance are enormous. By collecting and analysing substantial amounts of data, firms can discern what works for their customer needs and update existing products while innovating new ones. Notwithstanding the evidence about the effects of big data analytics, the link between big data analytics and innovation performance is still underestimated. Especially in today's fast-changing and complicated environments, companies cannot simply take big data analytics as one innovative technical tool without fully understanding how to deploy it effectively.
Design/methodology/approach
This study tries to investigate this relationship by building on the knowledge absorptive capacity perspective. The authors conceptualized effective use of big data analytics tools as one general absorptive capacity rather than a simple technical element or skill. Specifically, effectively utilize big data analytics tools can provide values and insights for new product innovation performance in a turbulent environment. Using online survey data from 108 managers, the authors assessed their hypotheses by applying the structural equation modelling method.
Findings
The authors found that big data analytics capacity, which can be conceptualized as one absorptive capacity, can positively influence product innovation performance. The authors also found that environmental turbulence has strong moderation effects on these two main relationships.
Originality/value
These results establish big data analytics can be regarded as one absorptive capacity, which can positively boost an organization's innovation performance.
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Priyanka Kumari Bhansali, Dilendra Hiran and Kamal Gulati
The purpose of this paper is to secure health data collection and transmission (SHDCT). In this system, a native network consists of portable smart devices that interact with…
Abstract
Purpose
The purpose of this paper is to secure health data collection and transmission (SHDCT). In this system, a native network consists of portable smart devices that interact with multiple gateways. It entails IoMT devices and wearables connecting to exchange sensitive data with a sensor node which performs the aggeration process and then communicates the data using a Fog server. If the aggregator sensor loses the connection from the Fog server, it will be unable to submit data directly to the Fog server. The node transmits encrypted information with a neighboring sensor and sends it to the Fog server integrated with federated learning, which encrypts data to the existing data. The fog server performs the operations on the measured data, and the values are stored in the local storage area and later it is updated to the cloud server.
Design/methodology/approach
SHDCT uses an Internet-of-things (IoT)-based monitoring network, making it possible for smart devices to connect and interact with each other. The main purpose of the monitoring network has been in the collection of biological data and additional information from mobile devices to the patients. The monitoring network is composed of three different types of smart devices that is at the heart of the IoT.
Findings
It has been addressed in this work how to design an architecture for safe data aggregation in heterogeneous IoT-federated learning-enabled wireless sensor networks (WSNs), which makes use of basic encoding and data aggregation methods to achieve this. The authors suggest that the small gateway node (SGN) captures all of the sensed data from the SD and uses a simple, lightweight encoding scheme and cryptographic techniques to convey the data to the gateway node (GWN). The GWN gets all of the medical data from SGN and ensures that the data is accurate and up to date. If the data obtained is trustworthy, then the medical data should be aggregated and sent to the Fog server for further processing. The Java programming language simulates and analyzes the proposed SHDCT model for deployment and message initiation. When comparing the SHDCT scheme to the SPPDA and electrohydrodynamic atomisation (EHDA) schemes, the results show that the SHDCT method performs significantly better. When compared with the SPPDA and EHDA schemes, the suggested SHDCT plan necessitates a lower communication cost. In comparison to EHDA and SPPDA, SHDCT achieves 4.72% and 13.59% less, respectively. When compared to other transmission techniques, SHDCT has a higher transmission ratio. When compared with EHDA and SPPDA, SHDCT achieves 8.47% and 24.41% higher transmission ratios, respectively. When compared with other ways it uses less electricity. When compared with EHDA and SPPDA, SHDCT achieves 5.85% and 18.86% greater residual energy, respectively.
Originality/value
In the health care sector, a series of interconnected medical devices collect data using IoT networks in the health care domain. Preventive, predictive, personalized and participatory care is becoming increasingly popular in the health care sector. Safe data collection and transfer to a centralized server is a challenging scenario. This study presents a mechanism for SHDCT. The mechanism consists of Smart healthcare IoT devices working on federated learning that link up with one another to exchange health data. Health data is sensitive and needs to be exchanged securely and efficiently. In the mechanism, the sensing devices send data to a SGN. This SGN uses a lightweight encoding scheme and performs cryptography techniques to communicate the data with the GWN. The GWN gets all the health data from the SGN and makes it possible to confirm that the data is validated. If the received data is reliable, then aggregate the medical data and transmit it to the Fog server for further process. The performance parameters are compared with the other systems in terms of communication costs, transmission ratio and energy use.
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Indrit Troshani and Nick Rowbottom
Information infrastructures can enable or constrain how companies pursue their visions of sustainability reporting and help address the urgent need to understand how corporate…
Abstract
Purpose
Information infrastructures can enable or constrain how companies pursue their visions of sustainability reporting and help address the urgent need to understand how corporate activity affects sustainability outcomes and how socio-ecological challenges affect corporate activity. The paper examines the relationship between sustainability reporting information infrastructures and sustainability reporting practice.
Design/methodology/approach
The paper mobilises a socio-technical perspective and the conception of infrastructure, the socio-technical arrangement of technical artifacts and social routines, to engage with a qualitative dataset comprised of interview and documentary evidence on the development and construction of sustainability reporting information.
Findings
The results detail how sustainability reporting information infrastructures are used by companies and depict the difficulties faced in generating reliable sustainability data. The findings illustrate the challenges and measures undertaken by entities to embed automation and integration, and to enhance sustainability data quality. The findings provide insight into how infrastructures constrain and support sustainability reporting practices.
Originality/value
The paper explains how infrastructures shape sustainability reporting practices, and how infrastructures are shaped by regulatory demands and costs. Companies have developed “uneven” infrastructures supporting legislative requirements, whilst infrastructures supporting non-legislative sustainability reporting remain underdeveloped. Consequently, infrastructures supporting specific legislation have developed along unitary pathways and are often poorly integrated with infrastructures supporting other sustainability reporting areas. Infrastructures developed around legislative requirements are not necessarily constrained by financial reporting norms and do not preclude specific sustainability reporting visions. On the contrary, due to regulation, infrastructure supporting disclosures that offer an “inside out” perspective on sustainability reporting is often comparatively well developed.
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Rajesh Chidananda Reddy, Debasisha Mishra, D.P. Goyal and Nripendra P. Rana
The study explores the potential barriers to data science (DS) implementation in organizations and identifies the key barriers. The identified barriers were explored for their…
Abstract
Purpose
The study explores the potential barriers to data science (DS) implementation in organizations and identifies the key barriers. The identified barriers were explored for their interconnectedness and characteristics. This study aims to help organizations formulate apt DS strategies by providing a close-to-reality DS implementation framework of barriers, in conjunction with extant literature and practitioners' viewpoints.
Design/methodology/approach
The authors synthesized 100 distinct barriers through systematic literature review (SLR) under the individual, organizational and governmental taxonomies. In discussions with 48 industry experts through semi-structured interviews, 14 key barriers were identified. The selected barriers were explored for their pair-wise relationships using interpretive structural modeling (ISM) and fuzzy Matriced’ Impacts Croise's Multiplication Appliquée a UN Classement (MICMAC) analyses in formulating the hierarchical framework.
Findings
The lack of awareness and data-related challenges are identified as the most prominent barriers, followed by non-alignment with organizational strategy, lack of competency with vendors and premature governmental arrangements, and classified as independent variables. The non-commitment of top-management team (TMT), significant investment costs, lack of swiftness in change management and a low tolerance for complexity and initial failures are recognized as the linkage variables. Employee reluctance, mid-level managerial resistance, a dearth of adequate skills and knowledge and working in silos depend on the rest of the identified barriers. The perceived threat to society is classified as the autonomous variable.
Originality/value
The study augments theoretical understanding from the literature with the practical viewpoints of industry experts in enhancing the knowledge of the DS ecosystem. The research offers organizations a generic framework to combat hindrances to DS initiatives strategically.
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Luís Oscar Silva Martins, Inara Rosa de Amorim, Vinicius de Araújo Mendes, Marcelo Santana Silva, Francisco Gaudencio Mendonça Freires and Ednildo Andrade Torres
This study aims to examine the price and income elasticities of short- and long-run industrial electricity demand in Brazil between 2003 and 2020. The research also examines the…
Abstract
Purpose
This study aims to examine the price and income elasticities of short- and long-run industrial electricity demand in Brazil between 2003 and 2020. The research also examines the impacts of COVID-19 in Brazil’s industrial electricity sector, including an analysis in states more and less industrialized.
Design/methodology/approach
Dynamic adjustments models in panel data are used to present robust estimates and analyze the impact of different methodologies on reported elasticities.
Findings
The short-run price elasticity is estimated at −0.448, while the long-run values are around −1.60. Regarding income elasticity, the value is 0.069 in the short-run and is concentrated in 0.25 in the long-run. The inelastic results of income show that the industrial demand for electric energy follows the trend of loss of competitiveness of the Brazilian industry in the past years. In addition, the price of natural gas, the level of employment, and, in specific cases, the level of imports also influence industrial electricity demand.
Originality/value
The research is a pioneer in the investigation of the industrial behavior of electricity of the Brazilian industrial branch, using as control variables, the average temperature, and the level of rainfall, this one, so important for a country whose main source is hydroelectric. In addition, to the best of the authors’ knowledge, it is the first study, which is prepared to analyze the effects of COVID-19 on electric consumption in the industrial sector, investigating these impacts, including in the states considered more and less industrialized. The estimates generated may help in the design of the Brazilian energy policy.
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Jin Xu, Pei Hua Shi and Xi Chen
This study aims to unveil the pivotal components and implementation pathways in the digital innovation of smart tourism destinations, while constructing a theoretical framework…
Abstract
Purpose
This study aims to unveil the pivotal components and implementation pathways in the digital innovation of smart tourism destinations, while constructing a theoretical framework from a holistic perspective.
Design/methodology/approach
The research focuses on 31 significant urban smart tourism destinations in China. Secondary data was collected through manual search supplemented by big data scraping, whereas primary data was obtained from interviews with municipal tourism authorities. Grounded theory was used to theoretically construct the phenomenon of digital innovation in smart tourism destinations.
Findings
This research has formulated a data-driven knowledge framework for digital innovation in smart tourism destinations. Core components include digital organizational innovation, smart data platforms, multi-stakeholder digital collaborative ecosystem and smart tourism scenario systems. Destinations can achieve smart tourism scene innovation through closed innovation driven by smart data platforms or open innovation propelled by a multi-stakeholder digital collaborative ecosystem.
Practical implications
Based on insights from digital innovation practices, this study proposes a series of concrete recommendations aimed at assisting Destination Management Organizations in formulating and implementing more effective digital innovation strategies to enhance the sustainable digital competitiveness of destinations.
Originality/value
This study advances smart tourism destination innovation research from localized thinking to systemic thinking; extends digital innovation theory into the realm of smart tourism destination innovation; repositions the significance of knowledge in smart tourism destination innovation; and constructs a comprehensive framework for digital innovation in smart tourism destinations.
目的
本研究致力于揭示智能旅游目的地数字创新中的核心组件及实施路径, 并创建一个整体视角下的理论框架。
设计/方法/方法
研究选定中国31座重要城市型智能旅游目的地为研究对象。通过人工检索结合大数据抓取的方式收集二手资料, 以各市旅游主管部门为访谈对象收集一手资料。运用扎根理论对智能旅游目的地的数字创新现象进行理论构建。
发现
本研究构建了一个数据型知识驱动的智能旅游目的地数字创新框架。其中, 核心组件包括数字组织创新、智慧数据平台、多主体数字协同生态和智慧旅游场景体系。目的地可通过智慧数据平台驱动的内生型创新或多主体数字协同生态推动的开放式创新, 实现智能旅游场景创新。
原创性/价值
本研究将智能旅游目的地创新相关研究由局部思考推向系统思考; 将数字创新理论扩展到智能旅游目的地创新的研究中; 重新定位知识在智能旅游目的地创新中的重要地位; 以及构建了一个智能旅游目的地数字创新整体框架。
实践意义
本研究基于数字创新实践洞察, 提出了一系列具体建议。旨在帮助目的地管理组织更有效地制定和实施数字创新策略, 以增强旅游目的地可持竞争力。
Diseño/metodología/enfoque
La investigación se centra en 31 destacados destinos turísticos urbanos inteligentes de China. Los datos secundarios se recopilaron mediante una búsqueda manual complementada con técnicas de big data, mientras que los datos primarios se obtuvieron a partir de entrevistas con las autoridades turísticas municipales. Se empleó la teoría fundamentada para construir teóricamente el fenómeno de la innovación digital en los destinos turísticos inteligentes.
Objetivo
Esta investigación tiene como objetivo identificar los componentes esenciales y las rutas de implementación de la innovación digital en destinos turísticos inteligentes, y construir un marco teórico desde una perspectiva holística.
Resultados
Este estudio ha desarrollado un marco de conocimiento basado en datos para la innovación digital en destinos turísticos inteligentes. Los componentes centrales incluyen la innovación organizativa digital, la plataforma de datos inteligentes, el ecosistema digital colaborativo de múltiples actores y el sistema de escenarios turísticos inteligentes. Además, tanto la innovación endógena impulsada por la plataforma de datos inteligentes como la innovación abierta impulsada por el ecosistema digital colaborativo de múltiples actores contribuyen a la innovación por escenarios en destinos turísticos inteligentes.
Implicaciones prácticas
A partir de las prácticas de innovación digital, este estudio ofrece una serie de recomendaciones dirigidas a las Organizaciones de Gestión de Destinos (DMOs) para la formulación e implementación de estrategias de innovación digital de manera más efectiva, y mejorar la competitividad digital sostenible de los destinos turísticos.
Originalidad/valor
Este estudio avanza la investigación sobre innovación en destinos turísticos inteligentes desde el pensamiento localizado hasta el pensamiento sistémico; extiende la teoría de la innovación digital al ámbito de la innovación en destinos turísticos inteligentes; reposiciona la importancia del conocimiento en la innovación de destinos turísticos inteligentes; y construye un marco integral para la innovación digital en destinos turísticos inteligentes.
Details
Keywords
- Smart tourism destination
- Smart tourism
- Digital innovation
- Destination innovation management
- Tourism digital innovation
- Tourism innovation
- :智能旅游目的地
- 智慧旅游
- 数字创新
- Destino turístico inteligente
- Turismo inteligente
- Innovación digital
- Innovación digital turística
- Innovación turística
- Gestión de la innovación en destinos
Yelena Smirnova and Victoriano Travieso-Morales
The general data protection regulation (GDPR) was designed to address privacy challenges posed by globalisation and rapid technological advancements; however, its implementation…
Abstract
Purpose
The general data protection regulation (GDPR) was designed to address privacy challenges posed by globalisation and rapid technological advancements; however, its implementation has also introduced new hurdles for companies. This study aims to analyse and synthesise the existing literature that focuses on challenges of GDPR implementation in business enterprises, while also outlining the directions for future research.
Design/methodology/approach
The methodology of this review follows the preferred reporting items for systematic reviews and meta-analysis guidelines. It uses an extensive search strategy across Scopus and Web of Science databases, rigorously applying inclusion and exclusion criteria, yielding a detailed analysis of 16 selected studies that concentrate on GDPR implementation challenges in business organisations.
Findings
The findings indicate a predominant use of conceptual study methodologies in prior research, often limited to specific countries and technology-driven sectors. There is also an inclination towards exploring GDPR challenges within small and medium enterprises, while larger enterprises remain comparatively unexplored. Additionally, further investigation is needed to understand the implications of emerging technologies on GDPR compliance.
Research limitations/implications
This study’s limitations include reliance of the search strategy on two databases, potential exclusion of relevant research, limited existing literature on GDPR implementation challenges in business context and possible influence of diverse methodologies and contexts of previous studies on generalisability of the findings.
Originality/value
The originality of this review lies in its exclusive focus on analysing GDPR implementation challenges within the business context, coupled with a fresh categorisation of these challenges into technical, legal, organisational, and regulatory dimensions.
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Haobo Zou, Mansoora Ahmed, Syed Ali Raza and Rija Anwar
Monetary policy has major impacts on macroeconomic indicators of the country. Accordingly, uncertainty regarding monetary policy shifts can cause challenges and risks for…
Abstract
Purpose
Monetary policy has major impacts on macroeconomic indicators of the country. Accordingly, uncertainty regarding monetary policy shifts can cause challenges and risks for businesses, financial markets and investors. Thus, the purpose of this study is to investigate how real estate market volatility responds to monetary policy uncertainty.
Design/methodology/approach
The GARCH-MIDAS model is applied in this study to investigate the nexus between monetary policy uncertainty and real estate market volatility. This model was fundamentally instituted to accommodate low-frequency variables.
Findings
The results of this study reveal that increased monetary policy uncertainty highly affects the volatility in real estate market during the peak period of COVID-19 as compared to full sample period and COVID-19 recovery period; hence, a significant decline is evident in real estate market volatility during crisis.
Originality/value
This study is particularly focused on peak and recovery period of COVID-19 considering the geographical region of Greece, Japan and the USA. This study provides a complete perspective on the nexus between monetary policy uncertainty and real estate markets volatility in three distinct economic views.
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Hailu Getnet, Aron O’Cass, Vida Siahtiri and Hormoz Ahmadi
This study aims to investigate the role of team problem-solving creativity in new product development (NPD) in the bottom-of-the-pyramid (BoP) in business-to-business firms. This…
Abstract
Purpose
This study aims to investigate the role of team problem-solving creativity in new product development (NPD) in the bottom-of-the-pyramid (BoP) in business-to-business firms. This study synthesizes perspectives from NPD, creativity and leadership to examine how work-related factors such as NPD managers’ role ambiguity and individual-related factors such as CEO’s ambidextrous leadership style interact to determine team problem-solving creativity and its effect on new product performance (NPP).
Design/methodology/approach
The hypotheses are tested using data from a multi-informant survey of 274 middle-level managers within 137 local BoP manufacturing firms in a sub-Saharan African country.
Findings
The results show that an NPD team’s ability to solve problems creatively determines NPP in BoP markets. The findings also show that NPD managers’ role ambiguity has a negative effect on team problem-solving creativity. However, a CEO’s ambidextrous leadership neutralizes the negative impact of role ambiguity on problem-solving creativity.
Originality/value
This study combines three distinct streams of literature, including NPD, creativity and leadership, to explore the antecedents and outcomes of problem-solving creativity. Drawing on creativity and leadership theories, this study reports that the success of creative idea exchanges depends heavily on a supportive environment for NPD team members and minimizing the NPD manager’s role ambiguity.
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The increasing adoption of informatization in the architecture, engineering, and construction (AEC) industries has raised the competency requirements for AEC practitioners…
Abstract
Purpose
The increasing adoption of informatization in the architecture, engineering, and construction (AEC) industries has raised the competency requirements for AEC practitioners. However, existing research primarily focuses on the integration of emerging technologies in AEC education programs, with little attention to the development of informatization-related competencies. Therefore, this paper aims to explore the competency requirements in the information age of the AEC industry.
Design/methodology/approach
Taking a policy perspective, this study investigates the competency requirements within the context of AEC industry informatization. By employing a competency-based theoretical framework, content analysis is conducted on China's policy document, the Outline of the Development of Informatization in the Construction Industry.
Findings
The study identifies crucial emerging technologies in the AEC industry, such as building information modeling (BIM), Big Data, Internet of things, networking, and cloud computing, along with their application scenarios. It considers various market players, including survey and design institutes, construction companies, and general contracting enterprises. Comparative analysis reveals the technology application patterns of these market players, shedding light on their preferences and perspectives. Based on these findings, the study proposes recommendations for competency requirements in the AEC industry.
Originality/value
This study extends the competency-based theory to AEC education from a macro perspective. The findings enhance understanding of informatization by providing insights into the related technologies, their applications, and the market players utilizing them. Moreover, the study's results have significant implications for AEC education, particularly in the design of curriculum systems for emerging technology-related fields.
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