Performance effects of technology–organization–environment openness, service co-production, and digital-resource readiness: The case of the IT industry

Adoption of artificial intelligence (AI) based employee experience (EEX) chatbots

Purpose

AI-based chatbots are revamping employee communication in organizations. This paper examines the adoption of AI-based employee experience chatbots by employees.

Design/methodology/approach

The proposed model is developed using behavioral reasoning theory and empirically validated by surveying 1,130 employees and data was analyzed with PLS-SEM.

Findings

This research presents the “reasons for” and “reasons against” for the acceptance of AI-based employee experience chatbots. The “reasons for” are – personalization, interactivity, perceived intelligence and perceived anthropomorphism and the “reasons against” are perceived risk, language barrier and technological anxiety. It is found that “reasons for” have a positive association with attitude and adoption intention and “reasons against” have a negative association. Employees' values for openness to change are positively associated with “reasons for” and do not affect attitude and “reasons against”.

Originality/value

This is the first study exploring employees' attitude and adoption intention toward AI-based EEX chatbots using behavioral reasoning theory.

Students' adoption of AI-based teacher-bots (T-bots) for learning in higher education

Purpose

The purpose of this paper is to investigate students' adoption intention (ADI) and actual usage (ATU) of artificial intelligence (AI)-based teacher bots (T-bots) for learning using technology adoption model (TAM) and context-specific variables.

Design/methodology/approach

A mixed-method design is used wherein the quantitative and qualitative approaches were used to explore the adoption of T-bots for learning. Overall, 45 principals/directors/deans/professors were interviewed and NVivo 8.0 was used for interview data analysis. Overall, 1,380 students of higher education institutes were surveyed, and the collected data was analyzed using the Partial Least Squares Structural Equation Modeling (PLS-SEM) technique.

Findings

The T-bot's ADI’s antecedents found were perceived ease of use, perceived usefulness, personalization, interactivity, perceived trust, anthropomorphism and perceived intelligence. The ADI influences the ATU of T-bots, and its relationship is negatively moderated by stickiness to learn from human teachers in the classroom. It comprehends the insights of senior authorities of the higher education institutions in India toward the adoption of T-bots.

Practical implications

The research provides distinctive insights for principals, directors and professors in higher education institutes to understand the factors affecting the students' behavioral intention and use of T-bots. The developers and designers of T-bots need to ensure that T-bots are more interactive, provide personalized information to students and ensure the anthropomorphic characteristics of T-bots. The education policymakers can also comprehend the factors of T-bot adoption for developing the policies related to T-bots and their implications in education.

Originality/value

T-bot is a new disruptive technology in the education sector, and this is the first step in exploring the adoption factors. The TAM model is extended with context-specific factors related to T-bot technology to offer a comprehensive explanatory power to the proposed model. The research outcome provides the unique antecedents of the adoption of T-bots.

Evaluating the adoption of cybersecurity and its influence on organizational performance

Cyberattacks negatively impact the performance of enterprises all around the globe. While organizations invest more in cybersecurity to avoid cyberattacks, studies on the factors affecting their overall cybersecurity adoption and awareness are sparse. In this paper, by integrating the diffusion of innovation theory (DOI), technology acceptance model (TAM), and technology-organization-environment (TOE) with the balanced scorecard approach, we propose a comprehensive set of factors that influence cybersecurity adoption and assess the effects of these factors on organizational performance. Data are collected through a survey of IT experts in small and medium-sized enterprises (SMEs) in the United Kingdom, with 147 valid responses. Structural equation modeling based on a statistical package for the social sciences (SPSS) was used to assess the model. The findings identify and confirm the importance of eight factors affecting SMEs' cybersecurity adoption. Moreover, cybersecurity technology adoption is found to positively impacts organizational performance. The proposed framework depicts variables influencing cybersecurity technology adoption and assesses their importance. The outcomes of this study provide a basis for future research and can be adopted by IT and cybersecurity managers to identify the most appropriate cybersecurity technologies that positively impact their company's performance.

Examining how and when digital platform capabilities drive technological innovation: a strategic information perspective

Purpose

This study aims to examine how and when digital platform capabilities drive technological innovation from a strategic information perspective, regarding information flow and information quality as mediators and business intelligence analytics as a moderator.

Design/methodology/approach

This study engaged corporate executives in surveys and obtained 182 firm data and then tested the hypotheses using linear regression models and the robustness using the structural equation model.

Findings

Digital platform capabilities drive corporate technological innovation through access to strategic information, i.e. strategic information mediates between digital platform capabilities and technological innovation. Business intelligence analytics increases the influence of strategic information on technological innovation.

Practical implications

This study underlines the importance for companies to construct digital platform capabilities to access strategic information to achieve technological innovation and the role of business intelligence analytics in processing strategic information.

Originality/value

This study finds a new perspective, strategic information, to explain the mechanisms by which digital platform capabilities drive firms’ technological innovation. In addition, the robustness of the resource-based view in understanding digital platform capabilities is stressed.

Design a technology acceptance model by applying system dynamics: an analysis based on key dimensions of employee behavior

Purpose

This study aims to investigate the impact of new technologies on parameters of organizational behavior and evaluate their determining role of technology maturity and readiness of staff in the digital readiness.

Design/methodology/approach

This study has obtained an integrated model of technology’s effect on staff’s organizational behavior considering digital readiness level by using system dynamics is developed. In this model, the effects of new technologies entry on organizational behavior variables are analyzed in different layers, and the result of this impact on the consequent of a bank organizational behavior and each indicator is examined separately in different scenarios. In determining the indicators and their significant coefficients, the viewpoints of banking experts and professionals in organizational behavior have been considered.

Findings

As a result of our surveys, five technology effects, without intermediaries, were obtained, which are automation, learning, streamlining repetitive jobs, addiction to technology and reducing face-to-face contact. Each of these factors would make a chain of side effects. In a way that, ultimately, their positive or negative effects on productivity and consequently on organization profits appear. The result indicates technology has effects on important behavioral factors such as stress, motivation, organization values and personal satisfaction. Indicators, which are formed by positive or negative factors, are being upgraded or downgraded. Therefore, managing negative cycles and developing positive cycles can be considered as one of the major banking concerns for controlling IT effects on its organizational behavior of human resources.

Originality/value

There is little academic remarkable literature on clarifying the effects of digitalization on employee's behavior in an organization, this research offers managers and organizations a model of influential factors that need to be taken into account by managers when they encounter new technologies. This study’s proposed analysis is useful to improve the efficiency and productivity of the organization, and alongside this, it is effective for the digital transformation process. This study fills previous research gaps in the academic context related to the practical studies that relied on digital maturity.

SMEs Performance in Malaysia: The Role of Contextual Ambidexterity in Innovation Culture and Performance

Small and medium-sized enterprises (SMEs) in both the industrial and service sectors have been identified as the drivers of Malaysia’s fast economic growth. However, SMEs are faced with an inherent issue of lack of resources and capabilities which constrains the ability of SMEs to improve performance. Due to this, it is critical for SMEs to understand and develop an important capability that supports them in facing a dynamic and competitive business environment. This study examines the mediating role of contextual ambidexterity as a dynamic capability in the relationship between innovation culture and SME performance. The online surveys were carried out starting from 5th July until 25th July 2021. A total of 277 SMEs in Selangor, Malaysia participated in this study and Covariance-Based Structural Equation modeling analysis was utilized to test the hypotheses. The findings show that in terms of direct relationships, innovation culture has a significant positive relationship with contextual ambidexterity, while innovation culture and contextual ambidexterity have a significant positive relationship with SME performance. The findings showed that contextual ambidexterity is significant as a mediator in the relationship between innovation culture and SME performance. This study makes an important contribution to the management field by highlighting the role of contextual ambidexterity, which is often the focus of large companies. These findings support the notion of dynamic capability that accentuates the importance of developing capabilities in dealing with dynamic and challenging situations.

Digital Resources Integration and Performance Evaluation Under the Knowledge Management Model in Academic Libraries

Leveraging a knowledge management model (KMM), organizing digital resources, and measuring performance beyond digital libraries continue to be hot topics for many organizations. Given its growing importance, the aim of this study was to design a robust integrated research model based on social cognitive theory and KMM to organize resources and improve the productivity of academic librarians to make services effective. Using a quantitative method based on key data collected by librarians at Pakistani universities, the researchers reviewed previously published literature and sought expert opinions to develop a research tool. The authors distributed 350 printed questionnaires to professionals from 190 universities, of which 339 were returned. These were analyzed to test the hypotheses and assess the accuracy of the measurement and structural models. After undergoing rigorous statistical analysis, the seven constructs using Social Cognitive Theory and the Knowledge Management Model have proven to be suitable for digital asset integration, employee productivity measurement, and high-quality academic services. In addition, the model based on social cognitive theory supports the application of KMM to promote knowledge culture, resource organization, and successful integration and innovation of academic services by enhancing the technical and professional skills of staff in academic institutions.

Opinion mining towards blockchain technology adoption for accessing digital library resources

Purpose

Blockchain technology is a distributed and decentralized public digital ledger, which is employed to save dynamic transaction data and static records across several computers so that each record could not be modified retroactively without the collusion of the network and alteration of all subsequent blocks. Recently, it has become immensely popular in digital resource sharing in different research areas such as healthcare, smart cities, cryptocurrency and libraries. Since the current eLibrary systems are vulnerable to issues such as unauthorized access, plagiarism, etc., there is a lack of access control system that can efficiently address these issues.

Design/methodology/approach

The authors designed a conceptual model for evaluating the users' intention in the use of blockchain-based digital libraries, which can facilitate the resource organization and provide additional security to interactive processes between users. To conduct our survey, the authors devised and shared two versions, English and Chinese, among 298 participants. Moreover, 7 PhD students participated in the pre-testing of the questioner design. The authors analyzed the demographic data using the Jamovi software and SmartPLS in order to generate the path modeling.

Findings

This study revealed that blockchain technology adaption in eLibraries is essential for enhancing the quality of services, infrastructure and resources for libraries. The study’s results show that optimism, informativeness, perceived usefulness, perceived ease of use, attitude and intention to use blockchain technology for accessing digital resources in libraries.

Originality/value

This study contributes to the adoption of blockchain technology in the digital library. To the best of the authors’ knowledge, this work is the first empirical attempt to provide a new perspective of developing digital libraries based on security policies. This model shows the underpinning knowledge to manage digital resources, which can facilitate the design phases and enhance the management costs in eLibraries.

Institutional pressure and open innovation: the moderating effect of digital knowledge and experience-based knowledge

Purpose

When considering the influence of external social, technical and political environments on organizations’ open innovation behavior, especially in emerging markets, institutional theory is especially salient. This study aims to answer the question of how to integrate organizations’ external institutional pressures and internal knowledge structure to mitigate the challenges in the open innovation process.

Design/methodology/approach

This study uses a sample of 2,126 observations from the 2012 World Bank Enterprise Survey. A multivariate regression model is designed to explore the impact of external institutional pressure (i.e. coercive pressure, mimetic pressure and normative pressure) on open innovation, as well as the moderating effect of digital knowledge and experience-based knowledge.

Findings

The results show that institutional pressure has a positive role in promoting open innovation; digital knowledge weakens the positive relationship between institutional pressure and open innovation; experience-based knowledge strengthens the positive relationship between institutional pressure (especially coercive pressure) and open innovation.

Originality/value

This study combines institutional theory and knowledge management to enriches insights into open innovation in emerging markets. Beyond recognizing the inherent multidimensionality of the concept of institutional pressure, this study creates an integrated path for the legitimacy acquiring of enterprises through the knowledge structure design (i.e. digital knowledge and experience-based knowledge). It also deepens the institutional pressure to enable the implementation of digital knowledge to manage open innovation processes.

Adoption of artificial intelligence (AI) for talent acquisition in IT/ITeS organizations

Purpose

Human resource managers are adopting AI technology for conducting various tasks of human resource management, starting from manpower planning till employee exit. AI technology is prominently used for talent acquisition in organizations. This research investigates the adoption of AI technology for talent acquisition.

Design/methodology/approach

This study employs Technology-Organization-Environment (TOE) and Task-Technology-Fit (TTF) framework and proposes a model to explore the adoption of AI technology for talent acquisition. The survey was conducted among the 562 human resource managers and talent acquisition managers with a structured questionnaire. The analysis of data was completed using PLS-SEM.

Findings

This research reveals that cost-effectiveness, relative advantage, top management support, HR readiness, competitive pressure and support from AI vendors positively affect AI technology adoption for talent acquisition. Security and privacy issues negatively influence the adoption of AI technology. It is found that task and technology characteristics influence the task technology fit of AI technology for talent acquisition. Adoption and task technology fit of AI technology influence the actual usage of AI technology for talent acquisition. It is revealed that stickiness to traditional talent acquisition methods negatively moderates the association between adoption and actual usage of AI technology for talent acquisition. The proposed model was empirically validated and revealed the predictors of adoption and actual usage of AI technology for talent acquisition.

Practical implications

This paper provides the predictors of the adoption of AI technology for talent acquisition, which is emerging extensively in the human resource domain. It provides vital insights to the human resource managers to benchmark AI technology required for talent acquisition. Marketers can develop their marketing plan considering the factors of adoption. It would help designers to understand the factors of adoption and design the AI technology algorithms and applications for talent acquisition. It contributes to advance the literature of technology adoption by interweaving it with the human resource domain literature on talent acquisition.

Originality/value

This research uniquely validates the model for the adoption of AI technology for talent acquisition using the TOE and TTF framework. It reveals the factors influencing the adoption and actual usage of AI technology for talent acquisition.

Big data analytics adoption model for small and medium enterprises

Purpose

Big data analytics (BDA) is recognized as a turning point for firms to improve their performance. Although small- and medium-sized enterprises (SMEs) are crucial for every economy, they are lagging far behind in the usage of BDA. This study aims to provide a single and unified model for the adoption of BDA among SMEs with the integration of the technology–organization–environment (TOE) model and resource-based view.

Design/methodology/approach

A survey of 112 manufacturing SMEs in Iran was conducted, and the data were analysed using structural equation modelling to test the model of this study.

Findings

The results offer evidence of a BDA mediation effect in the relationship between technological, organizational and environmental contexts, and SMEs performance. The findings also demonstrated that technological and organizational elements are the more significant determinants of BDA adoption in the context of SMEs. In addition, the result of this study confirmed that BDA adoption could enhance the financial and market performance of SMEs.

Practical implications

Providing a single unified framework of BDA adoption for SMEs enables them to appreciate the importance of most influential elements (technology, organization and environment) in the adoption of BDA. Also, this study may encourage SMEs to be more willing to use BDA in their businesses.

Originality/value

Although there are studies on BDA adoption and firm performance among large companies, there is a lack of empirical research on SMEs, in particular, based on the TOE model. SMEs differ from large companies in terms of the availability of resources and size. Therefore, this study aimed to initiate a conceptual framework of BDA adoption for SMEs to assist them to be able to take advantage of the adoption of such technology.

Adoption of internet of things (IoT) in the agriculture industry deploying the BRT framework

Purpose

The purpose of this paper is to investigate the adoption of Internet of Things (IoT) in the agriculture industry by the farmers' in India using the theoretical lens of the behavioral reasoning theory (BRT).

Design/methodology/approach

A survey on farmers was conducted to examine the adoption of IoT in agriculture industry (IoT-A) using BRT. The data analysis of the primary survey was done by applying the structural equation modelling (SEM) technique.

Findings

The ‘reasons for’ adoption of IoT-A were as follows: Relative advantage, social influence, perceived convenience, and perceived usefulness. The ‘reasons against’ adoption were as follows: Image barrier, technological anxiety, perceived price and perceived risk. The BRT theory provides the platform to discuss the psychological processing of acceptance of IoT in agriculture industry by the farmers.

Practical implications

This research has unique implications as it studies the rural consumers’ behavior of innovation adoption namely IoT in agriculture. It provides the specific reasons ‘for’ and ‘against’ IoT adoption in agriculture, which will give directions to the marketers of IoT technology to develop suitable marketing strategies to improve the adoption in rural areas.

Originality/value

This research takes the first step in the direction toward deliberation of the adoption of IoT-A by farmers in an emerging Indian economy using the BRT theory, which discusses the ‘reasons for’ and ‘reasons against’ adoption in a proposed model.

An empirical study on the online learning experience of MOOCs: Indian students’ perspective

Purpose

The purpose of this paper is to investigate the online learning experience (LE) of massive open online courses (MOOCs) among the students in India using the lens of community of inquiry (CoI) model and two additional contextual factors.

Design/methodology/approach

The study conducted a survey using a structured questionnaire among the undergraduate and postgraduate students to examine the LE of MOOCs using the CoI framework and contextual variables – technical barrier (TB) and hedonic motivation (HD). The primary data were analyzed with the partial least squares structural equation modeling technique.

Findings

The results show that teaching presence (TP) influences cognitive presence (CP) and social presence (SP). SP influences CP. It is also found that TP, SP and CP influence the LE of MOOCs. It is found that TB negatively influences LE but is not significant and HD significantly influences LE positively for MOOCs.

Research limitations/implications

This study has a few limitations as it is a cross-sectional study in India, which surveyed undergraduate and postgraduate MOOCs learners, and caution needs to be taken while generalizing the outcomes. Further studies can be conducted across other countries considering demographic factors like age, gender, income groups, education and profession.

Practical implications

This research highlights the antecedents influencing the LE of MOOC learners using the CoI framework which will help the MOOC designers and marketers to apprehend the factors influencing LE. The results of this research will help them formulate suitable strategies in the design and delivery of MOOCs to improve the LE of learners.

Originality/value

This unique research investigates and empirically validates the CoI framework to understand LE of MOOC learners in India. This research extends the CoI framework by adding contextual factors – TB and HD in the context of a developing country.