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This paper aims to explore the influence of spatial dynamics on street vendors and examines the insecurities and coping mechanisms they faced and adopted during the pandemic. It examines the precarious nature of street vending during a global economic shock, highlighting the vulnerabilities and resilience of this informal sector.

This study uses a case study approach, conducting semi-structured face-to-face interviews with 74 street vendors in two key markets: Bara Bazaar (natural market) and Treasury Square (non-natural). The authors use the Gioia method, renowned for its systematic rigour in exploring the challenges and adaptations of street vendors during periods of economic uncertainty and crisis.

This study reveals that COVID-19 lockdowns profoundly impacted the security of tribal street vendors operating in natural and non-natural markets. It sheds light on the mechanism of shadow security, observed as a form of diverse coping mechanisms adopted by vendors during the pandemic, such as collective fund pooling, poultry farming and adapting new business models – from changing the goods they sell to transitioning between regular and mobile vending or from retail shops to street vending.

This study used the grounded theory framework of sustainable livelihood strategies and explores how street vendors can achieve sustainability through street vending. It further proposes recommendations for urban policies tailored across various dimensions.

This paper highlights indigenous mechanisms to secure livelihoods, which act as safety nets and facilitate a form of shadow security. The paper also determines how the spatial dynamics of a vending location can preferably change the security of the street vendors in times of crisis. This research challenges the oversimplified notion that the social security of street vendors cannot be neatly categorised as secure or insecure. Instead, it underscores vendors’ dynamic strategies and resilience to sustain their livelihoods amidst economic disruptions.

Agriculture diversification acts as income enhancing as well as distress mitigating strategy. India has witnessed rise in per-capita income which in turn has increased the demand for food particularly high-valued food items but agricultural production has failed to keep pace with the growing demand. The purpose of this paper is to examine spatio-temporal variations in agricultural diversification (AD) in India. Second, the authors try to identify the determinants of AD. Third, the authors examine the convergence hypothesis with reference to agriculture diversification across Indian states.

The study is based on the panel data constituting 20 major states of India during 1990–1991 to 2013–2014. It uses Simpson Diversification Index to measure AD. The heteroskedasticity-corrected panel regression model is applied to find out the determinants of AD. The fixed-effects model is used to examine β-convergence in AD across the sample states. Alternative time series models are applied to examine σ-convergence in AD.

The rising per-capita income and urbanization are driving dietary diversity towards high-valued crops and providing ample opportunity for AD. But poor and inadequate cold storage facility and rising cost of cultivation are posing major hindrance to it. Small land holding and road length have negatively influenced AD which is contrary to the traditional wisdom. The study found divergence in diversification and rising inequality in diversification.

The study is based on secondary data. A primary study to complement this could have been better. It is only based on one country.

Food inflation has serious adverse effect on the society at large. It is necessary to promote AD for controlling food price inflation. Minimum support price provided by the government should be extended to all crops; otherwise, it will fuel inflation. Given the fact fragmentation of land holding is adversely affecting AD, community based farming and consolidation of farm land should be the way forward to improve farmers’ income as well as reduce risk.

To best of the authors’ study, this is the first study that examines determinants of AD and convergence in AD during the high growth period of India.

Despite India achieving many milestones under MGNREGA, the external and internal shocks result in below potential outcomes in employment demand and generation. This study examines how these shocks matter and how the migration-prone regions perform.

This study, employing district-level data from 2018 to 2021, investigates how climate change and COVID-19 have affected the employment demand and supply. We applied RE-GLS and IV-2SLS regressions to examine the effects of shocks on employment demand and generation, respectively. The difference in difference panel model is employed to test the spatial effects of the pandemic. Further, we used RE-GLS and extended regression model to examine how external shocks interacting with migration affect unemployment rates.

It was found that the pandemic increased employment demand and generation. This reflects the adverse effects of the pandemic and the swift action by the government. However, the responses were possibly different during climate shocks. The wage differential increased employment demand. However, demand decreased due to poor support from the support staff. The employment generation was higher in migration-prone districts, indicating that seasonal migration, being a lean-season phenomenon, continues to occur despite employment generation.

This study contributes to the literature in several ways. It captures spatial variations while examining the impact of climate change and COVID-19. It investigates the performance of MGNREGA in migration-prone areas. In effect, the findings provide policymakers with greater insight into the issues.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-02-2024-0132.

The purpose of this study is to gain meaningful insights into a microfinance programme in two different agro-ecological settings in India. The study, using primary survey data, attempts to examine individual, household and environmental characteristics that determine participation in a self-help group (SHG)–bank linkage programme in Odisha.

Primary data are collected by a stratified random sampling method. The sample size is 300 households and information is collected by canvassing a pre-designed schedule to women through door-to-door in-depth interviews. In addition, focus group discussions have been conducted to get qualitative information. A probit binary model is applied to examine the factors determining participation in a SHG–bank linkage programme. A composite index of women empowerment is computed taking three dimensions: autonomy, economic empowerment and the gender relationship. Further, ordinary least square multiple regression and treatment effect evaluation by propensity score matching is carried out to study the impact of participation on women empowerment.

The study finds that the programme has by-passed the poorest of the poor. It is observed, however, that participation in microfinance has a positive and significant impact on women empowerment.

Given the research methodology adopted in this study, one concern is whether the results generalise. Therefore, researchers are encouraged to test the proposed propositions further.

To improve status of women particularly in developing and underdeveloped regions, microfinance can act as a catalyst.

Microfinance in the form of SHG–bank linkage should be promoted, particularly for those social groups and religious communities where women are discriminated. Their participation in SHG–bank linkage programme will improve their social status through empowerment.

This study illustrates how microfinance can improve the status of women.

This study examines whether customer-perceived employee competence (CPEC) furthers customer loyalty through justice perception and affection, and whether gender and service failure moderate these relationships.

Data were collected from 535 customers of five Indian rural banks administering the questionnaire. The questionnaire gathered information on sociodemographics and measured constructs using standard inventories. The data were analyzed using structural equation modeling.

The results reveal that when the effects of age are controlled for, CPEC enhances attitudinal and behavioral loyalty. The effects of CPEC partially influence attitudinal and behavioral loyalty through justice perception and customer affection. Attitudinal loyalty also promotes behavioral loyalty. With a few exceptions, stronger (weaker) effects are observed for female (male) gender and low (high) service failure, including CPEC influencing loyalty and justice perception, justice perception impacting customer loyalty and affection, customer affection promoting loyalty and attitudinal loyalty furthering behavioral loyalty.

Customers need competent employees to address bank service failure. CPEC fosters justice perception and affection, which in turn increases customer loyalty to the bank.

The purpose of this paper is to discuss the trends in relative efficiency of software companies in India during 1999-2008 by applying input-oriented data envelopment analysis (DEA) model. Based upon the PROWESS Database of Centre for Monitoring Indian Economy (CMIE), the efficiencies were estimated for the Indian, multinational and group companies. Also, relationship between efficiency and size is examined.

The study applied DEA to measure relative efficiencies of software companies and two different DEA models, CCR and BCC, were applied to evaluate the relative efficiency of the sample software companies in India. Comparisons of efficiency scores based on ownership were carried out by applying ANOVA and t-statistics.

The mean overall technical efficiency (OTE) of the software industry in India during 1999-2008 was low at 0.477. The mean pure technical efficiency for the industry for the study period was found to be 0.654 suggesting that software firms, on an average, were wasting 35 per cent of their inputs. It was observed that the Indian-owned companies have relatively high OTE score as compared to foreign owned and group owned companies. The mean OTE score of PI companies was found to be greater than the other two categories. In terms of, size it is observed that medium sized companies performance better.

Software companies can use DEA to examine their performance against the best performers in the industry. Software industry in India, which is doted by large number of small firms in the lower part of the size pyramid, needs to increase their size to improve their efficiency.

Research on measurement of service sector export oriented industry efficiency is limited. This paper is one of the few published studies examined service sector performance. This paper fills the gap in the literature by applying DEA in software industry in India and compares performance in terms of ownership and size.