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This paper aims to provide a better understanding of the prolonged consumption journey and how they are sustained by service providers’ use of habit-boosting strategies. Existing research is critically evaluated, and a research agenda is provided to inspire and guide future research.

This paper develops a conceptual framework that integrates habit and transformative consumer intervention theories with customer journey literature to explain the role of habit in sustaining prolonged consumption journeys. Habit-boosting strategies are introduced as mechanisms for service providers to facilitate their customers’ prolonged consumption journeys.

This paper argues that habit strength is a limited operant resource that often lacks resource integration efficiency and hinders customers’ abilities to sustain prolonged consumption journeys. Four distinct habit-boosting strategies are identified that provide the potential for service providers to facilitate their customers’ prolonged consumption journeys.

This study presents a typology of habit-boosting strategies and a research agenda that discusses a range of practically relevant and theoretically insightful contributions.

Soft robots are known for their excellent safe interaction ability and promising in surgical applications for their lower risks of damaging the surrounding organs when operating than their rigid counterparts. To explore the potential of soft robots in cardiac surgery, this paper aims to propose an adaptive iterative learning controller for tracking the irregular motion of the beating heart.

In continuous beating heart surgery, providing a relatively stable operating environment for the operator is crucial. It is highly necessary to use position-tracking technology to keep the target and the surgical manipulator as static as possible. To address the position tracking and control challenges associated with dynamic targets, with a focus on tracking the motion of the heart, control design work has been carried out. Considering the lag error introduced by the material properties of the soft surgical robotic arm and system delays, a controller design incorporating iterative learning control with parameter estimation was used for position control. The stability of the controller was analyzed and proven through the construction of a Lyapunov function, taking into account the unique characteristics of the soft robotic system.

The tracking performance of both the proportional-derivative (PD) position controller and the adaptive iterative learning controller are conducted on the simulated heart platform. The results of these two methods are compared and analyzed. The designed adaptive iterative learning control algorithm for position control at the end effector of the soft robotic system has demonstrated improved control precision and stability compared with traditional PD controllers. It exhibits effective compensation for periodic lag caused by system delays and material characteristics.

Tracking the beating heart, which undergoes quasi-periodic and complex motion with varying accelerations, poses a significant challenge even for rigid mechanical arms that can be precisely controlled and makes tracking targets located at the surface of the heart with the soft robot fraught with considerable difficulties. This paper originally proposes an adaptive interactive learning control algorithm to cope with the dynamic object tracking problem. The algorithm has theoretically proved its convergence and experimentally validated its performance at the cable-driven soft robot test bed.

The present study is intended to assess the risk factors associated with digital buying. Also aims to design and develop an instrument to assess the digital buyers risk factor score (DBRFS) in light of pandemic.

Present investigation uses a quantitative approach to achieve the stated objectives. The survey instrument for the purpose of assessing risk factors associated with digital buying was developed in two phases. The present study adopts theory of planned behaviour (TPB), built based on the theory of reasoned action (TRA). The data were collected and analysed considering 500 valid responses, sampling unit being digital buyers using social media platforms in tyre-II city of India. The data collection was undertaken between June 2021 and August 2021. The instrument is designed and validated using exploratory factor analysis (EFA) followed by confirmatory factor analysis (CFA).

The present research identified six perceived risk factors that are associated with digital buying; contractual risk, social risk, psychological risk, perceived quality risk, financial risk and time risk. The DBRFS of male is 3.7585, while female is 3.7137. Thus, risk taking by the male and female is at par. For the age group 15–30, DBRFS is 3.6761, while age group 31–45 noted as 3.7889 and for the 46–50 age groups it is measured as 3.9649.

The marketers are expected to have the knowledge about how people responds to the pandemic. The outcome of the research helps to understand consumer behaviour but disentangling consumer’s “black box” is challenging especially during global distress. The present study outcome helps the digital shopkeepers to respond positively to meet the needs of digital buying.

The scale development and to quantify the DBRFS. A deeper understanding of about digital consumers during pandemics will help digital shopkeepers to connect issues related digital buying.

In this study, the authors examine the push and pull effects of extreme weather events on migration among governorates in Egypt.

To estimate the effect of extreme weather events on internal migration, the authors use migration gravity models and data from the 1996 and 2006 Population and Housing Censuses. The authors measure weather extremes by the number of months in the past 36 months with temperatures or precipitation of a governorate below the 5th percentile and above the 95th percentile of the distribution of monthly temperatures or precipitation of the corresponding governorate during the period 1900–2006.

This study’s results suggest that high temperatures in the origin area act as a push factor. High-temperature extremes have a positive effect on out-migration. A 1% increase in the number of months with high-temperature extremes in the original governorate results in a 0.1% increase in the number of out-migrants.

The study suggests that people may respond to weather extremes through migration. However, climate migrants in Egypt may encounter several significant risks that authorities must address.

This study is one of the first attempts to measure the push and pull effect of weather extremes on migration in Egypt.

This paper aims to investigate the attraction of cannabis-infused soft drinks beverages among young Canadian consumers in the wake of a rise in multimodal cannabis consumption. It is an area of accelerated growth potential, with little research data currently available, and findings would inform stakeholders in the soft drinks market. The research participants were all university students in Ontario province, Canada.

Random convenience sampling data collection techniques were used to gather data from the Ontario-based participants. Reliability, factors loading and multiple regression analysis were administered to understand the impact of factors towards positive attitude.

The results reveal that price, impulsive personality, social insecurity and social norms all have a positive influence towards positive attitude. However, energy, taste and past experience failed to show any relationship with positive attitude. The results suggest that the individual consumer’s personality and social context have greater influence than price, a useful insight into the market trends for stakeholders within the industry.

The use of convenience sampling, due to the potentially sensitivity nature of the area of study, hinders the use of a sampling frame.

To the best of the authors’ knowledge, this study is the first of its kind to examine positive attitude with respect to cannabis-infused soft drinks among young consumers in Canada. It is of particular interest to stakeholders in the production and marketing sectors of the global beverage industry, and its findings will help inform this fledgling wing of that industry on how to move forward through the unknown territory with regard to consumer motivations.

This research theoretically proposed and empirically validated a Customer-Based Brand Equity (CBBE) scale specifically for Medical Tourism for emerging economies including recent findings from tourism theories such as gravity model and signalling theory, but more specifically accommodating political, cultural, economic, legal and social influences.

In-depth literature reviews from tourism, medical tourism, healthcare and hospitality domains are used to propose the theoretical model. The authors have used the lavaan package in R for the empirical analysis and model verification.

The research included, tested and verified the established latent variables such as “brand awareness”, “brand association”, “perceived quality” and “loyalty”, along with new observed variables for the CBBE scale from the theoretical perspectives of this research. “Infrastructure” has emerged as a new scale construct and “culture” was found to be a moderating variable for “perceived quality” in the CBBE scale, which are novel additions to the literature.

The research contributed to scale refining, latent construct assessment, and fine-tuning of the observed variables for the mentioned theoretical gaps.