Digital resilience and new business models in the post-COVID-19 scenario: from B2B perspective in the era of knowledge economy

Purpose

The purpose of this study is to examine how the pandemic impacted on business-to-business (B2B) cooperation and coordination, as well as on firms' financial and operational performance, from the B2B context in the era of knowledge economy.

Design/methodology/approach

With the help of social network theory, coordination theory and existing literature, a theoretical model was developed conceptually. Later, the conceptual model was validated using structural equation modelling technique with consideration of 712 respondents from different firms who are engaged in managing B2B relationships on behalf of their firms.

Findings

The study found that the COVID-19 pandemic has had a considerable moderating impact on the relationship between B2B cooperation and coordination with B2B relationship satisfaction. The study also highlighted that there is a degradation of financial and operational performance of firms due to the impact of COVID-19 pandemic on their B2B relationship management.

Practical implications

There is a challenging and ever-evolving global economy caused by the COVID-19 pandemic. Although it is argued that the pandemic has accelerated the growth of some online firms, it has also had a catastrophic effect, culminating in many firms failing. This study has developed a new business model which helps in improving financial as well as operational performance of the firms in post COVID-19 scenario, especially in the era of knowledge economy.

Originality/value

This is a unique study as this study (1) develops a unique theoretical model with high explanative power, (2) demonstrates how digital reliance and new business model help the firms in post COVID-19 pandemic and (3) adds to the body of literature in the domain of digital reliance, knowledge economy and B2B relationship management.

Why Do People Use IoT-Enabled Devices?

The purpose of this paper is to identify factors predicting perceived intention of using IoT by Indians. To fulfill the purpose, basing on literature review and on diffusion theory of planned behavior (DTPB) model, factors predicting perceived intention of using IoT by the Indian consumers have been identified and hypotheses have been developed which were tested by collecting data using questionnaire from 400 concerned respondents. The data were analyzed and tested using different standard tools. The study revealed that: perceived usefulness, perceived ease of use, compatibility impact attitude, influence of family members, influence of peers, influence of others impact subjective norms, self-efficacy, and facilitating conditions impact perceived behavioral control. Again, attitude and perceived behavioral control influence intention though subjective norms significantly do not influence intention. Again, it is found that intention positively influences the actual use of IoT by the consumers. The outcome would help the IoT service providers to improve their businesses.

Dark side of instant messaging: an empirical investigation from technology and society perspective

Purpose

The purpose of this study is to examine the dark side of instant messaging from the technological and societal perspectives.

Design/methodology/approach

With the help of literature review and different theories, a model has been developed conceptually. Later the model has been validated using statistical method. The authors have used 304 responses from the survey method, and this sample has been used to statistically validate the conceptual model.

Findings

This paper has been able to explicitly investigate and identify how different instant messaging platforms such as WhatsApp, WeChat in the form of electronic word of mouth (e-WOM) are contributing toward increase of mob lynching cases. The paper also highlights the important to have effective and enforceable regulation to regulate instant messaging services to the citizens.

Research limitations/implications

The findings cannot be generalized as the data is collected from India only. Moreover, the study is cross-sectional in nature. To get the comprehensive results, a longitudinal study needs to be conducted. This study considered seven constructs with one moderator. Having more predictors with other boundary conditions might have increased the explanative power of the model.

Practical implications

Instant messaging platforms such as WhatsApp, WeChat and so on are disseminating quick unverified information to the common people. This information sometimes is disseminated in inappropriate and exaggerated forms. This makes the instant messaging (WhatsApp) users' sentiment readily heated in some cases. They take such an action as mob lynching. This study determines the predictors of mob lynching along with the moderator impact of instant messaging in the society.

Originality/value

There are only a few studies those have explored the dark side of instant messaging. The proposed theoretical model is a unique model, which shows the predictors of mob lynching along with the negative consequences of the instant messaging (WhatsApp) in the society. From this perspective, this study can be considered as a unique study.

Development and Implementation of a Hybrid Wireless Sensor Network of Low Power and Long Range for Urban Environments

The urban population, worldwide, is growing exponentially and with it the demand for information on pollution levels, vehicle traffic, or available parking, giving rise to citizens connected to their environment. This article presents an experimental long range (LoRa) and low power consumption network, with a combination of static and mobile wireless sensors (hybrid architecture) to tune and validate concentrator placement, to obtain a large coverage in an urban environment. A mobile node has been used, carrying a gateway and various sensors. The Activation By Personalization (ABP) mode has been used, justified for urban applications requiring multicasting. This allows to compare the coverage of each static gateway, being able to make practical decisions about its location. With this methodology, it has been possible to provide service to the city of Malaga, through a single concentrator node. The information acquired is synchronized in an external database, to monitor the data in real time, being able to geolocate the dataframes through web mapping services. This work presents the development and implementation of a hybrid wireless sensor network of long range and low power, configured and tuned to achieve efficient performance in a mid-size city, and tested in experiments in a real urban environment.

Personal Data Sharing and Legal Issues of Human Rights in the Era of Artificial Intelligence

Personal data sharing has become an important issue in public and private sectors of our society. However, data subjects are perceived to be always unwilling to share their data on security and privacy reasons. They apprehend that those data will be misused at the cost of their privacy jeopardising their human rights. Thus, personal data sharing is closely associated with human right issues. This concern of data subjects has increased manifolds owing to the interference of Artificial Intelligence (AI) since AI can analyse data without human intervention. In this background, this article has taken an attempt to investigate how applications of AI and imposition of regulatory controls with appropriate governance can influence the impact of personal data sharing on the issues of human right abuses.