Comparing Attribute Importance and Reason Methods for Understanding Behavior: An Application to Internet Job Searching

Multidimensional Deprivation from Labor Market Opportunities in Armenia: Evidence from 2018 and 2020

This paper explores the multidimensional deprivation from labor market opportunities in Armenia by constructing a Quality of Employment measure. Using Labor Force Survey datasets for the years 2018 and 2020, we conduct a comparative analysis for a group of job-separated individuals. The identified dimensions of deprivation from labor market opportunities prior to and after the onset of COVID-19 are reasons for separating from a job, reasons for not looking for a job, and main obstacles in finding a job. These dimensions enable to study employee-level (supply factors) and job-related characteristics (demand factors). Our study shows that demand factors are the primary drivers of amplified deprivation in times of the pandemic. Also, we observe that the gender gap in the labor market deprivation has been increased during the pandemic, further amplified for married women. Interestingly, gender gap in deprivation is invariant to the occupational composition.

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.

An intention to use mobile applications for medical supplies and equipment ordering in clinics

This research developed a mobile medical supplies and equipment ordering app (MMSEOA) model and attempted to validate it empirically. When customers (clinic doctors) make purchases on the app, two types of reasons can be identified: "reasons for" include enduring involvement (emotions), product description, and awareness (familiarity) while the "reasons against", were demonstrated as perceived risk and resistance to change (fear). This study aimed to strengthen and illuminate the most significant dimensions that enhance a doctor's understanding of MMSEOA and the intention to use it. Furthermore, this research investigated the model's applicability among clinic doctors in Jordan. The model was empirically examined using a sample of 342 Jordanian clinic doctors and their secretaries who use mobile services in general. The survey method, a quantitative approach, was utilized; the partial least squares structural equation modeling system was used to investigate the proposed framework. The results demonstrate that these "reasons for" positively influenced the intention to use the MMSEOA except product description. Similarly, reasons against negatively influence the customers' intention to use the MMSEOA app, while perceived risk had no effect on the intention to use. These findings suggested that researchers should focus more on the services, products, and the main function of the MMSEOA to determine their influences on customers' intention to use. This will improve the buying habits related to purchasing medical supplies using MMSEOA and other online platforms, specifically in Jordan and the Middle East at large.

Examining Green Hotel Patronage Intention from the Perspective of Behavioural Reasoning Theory

Green hotels help minimise the negative impact of consumption on the environment. This study examines consumers’ intention to patronise green hotels by applying the Behavioural Reasoning Theory (BRT). In the BRT, the drivers of behavioural intentions include value, reasons for, reasons against as well as global motives (attitude). This study surveyed 262 respondents in the Klang Valley, Malaysia using questionnaires. The findings indicated that reasons serve as essential linkages between consumers’ values and their attitudes. In particular, Attitude is the strongest predictor of green hotel patronage intention, followed by Reasons against Patronage, Altruism and Reasons for Patronage. Reasons against Patronage have a stronger influence on green hotel patronage intention than Reasons for Patronage. Marketers should minimise the effects of reasons against to improve green hotel patronage intention, promote consumer’s altruism value and attitude toward choosing green hotels.

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.

Adoption of internet of things (IOT) based wearables for healthcare of older adults – a behavioural reasoning theory (BRT) approach

Purpose

The purpose of this paper is to utilize the novel approach of applying the behavioral reasoning theory (BRT) to examine the adoption of internet of things (IoT) based wearables for the healthcare of older adults and it aims to understand the relative effect of “reasons for” and “reasons against” adoption of IoT-based wearables for health care among older adults.

Design/methodology/approach

The hypothesized relationships were established using the BRT and empirically tested using a representative sample of 815 respondents. The data were analyzed using the PLS-SEM method.

Findings

The findings of this study demonstrate that adoption intention of IoT-based wearables for the health care of older adults is influenced by “reason for” and “reason against” adoption. The finding shows that “reasons for” adoption are ubiquitous, relative advantage, compatibility and convenience and “reasons against” adoption are usage barrier, traditional barrier and risk barrier. Value of “openness to change” significantly influences the “reasons for” and “reasons against” adoption of IoT-based wearables.

Research limitations/implications

This cross-sectional study is conducted only in the Indian context and future research can be conducted in other countries to generalize the results.

Practical implications

This research highlighted both the adoption factors—“for” and “against,” which should be considered while developing marketing strategies for IoT-based wearables for health care of older adults. Adoption of IoT-based wearables for healthcare of older adults will increase when marketers endeavor to minimize the effects of the anti-adoption factors.

Originality/value

This is a unique study that examines the adoption of IoT-based wearables for healthcare among older people using the BRT, by probing the “reasons for” and “reasons against” adoption in a single framework.