Search results

As we reckon with the #MeToo movement, the gender-based violence that occurred during the 1947 Partition continues to remain forgotten in mainstream discourses and is an emotive and polarising issue within both India and its diaspora. Just like mainstream news in the United States covered the Gabby Petito case, causing a controversy as it led to the realisation that the rape and gender-based violence of missing indigenous women were not covered, it can be suggested that mainstream news channels both within India and in the diaspora construct narratives that privilege the stories of some over others – with issues of shame, izzat (‘honour’) and policing of women's bodies compounding the silence in South Asian communities. In this chapter, I argue that we need to rethink the Partition as a genocide to recognise the gender-based violence that occurred on women's bodies as the cataclysmic event occurred. I discuss the feminist historiographical research led by Urvashi Butalia, Kamla Bhasin and Ritu Menon who interviewed survivors in the aftermath of the 1984 anti-Sikh riots that triggered their research and reminded them of the Partition violence. It is only recently when the 1947 Partition Archives (in 2010) and the Partition Museum (in 2017) that the conversations of Partition are also taking place in academic spaces.

The heat transfer by radiation and natural convection in a two‐dimensional, air‐filled square enclosure with a vertical partition of finite thickness and varying height was investigated numerically in the laminar regime. The horizontal end walls are assumed to be adiabatic, and the vertical walls are at different temperatures. Calculations are made by using a finite volume method and an efficient numerical procedure is introduced for calculating the view factors, with shadow effects included. The results indicate that the partition does not significantly modify the heat transfer rate through the cavity, especially at high Rayleigh numbers, provided that its height is less than 90 per cent of the cavity height. The effects of radiation on the velocity and the temperature fields and the overall heat transfer rates as a function of the widths of the vents, solid/fluid conductivity ratio and Rayleigh number are documented.

Strategic positioning of foreign firms in a host market is vital for their success. By integrating the resource partitioning theory and the resource-based view, this study aims to investigate foreign firms’ strategic positioning (i.e. their choice of generalist or specialist positioning strategy) and its performance implications in the US market.

The final sample includes 212 foreign companies from 28 countries operating in the US market. Multiple data sources were used to collect data of these foreign companies’ subsidiaries in the USA This study used logistic regression to test its major hypotheses.

The results of this study suggest that a generalist positioning strategy is positively related to performance in a host market. It is also found that market concentration and local market knowledge moderate this strategic positioning – performance relationship.

For a foreign firm that enters a host market, market concentration (an industry-level factor) in the host market and the firm’s local market knowledge (a firm-specific factor) play prominent roles in the strategic positioning – performance relationship.

This study offers a novel perspective of international business strategy by applying the lens of resource partitioning theory to study the relationships between multinational enterprises’ strategic positioning and performance. This study contributes to the strategy literature in that it examines the performance implications of firms’ strategic positioning (i.e. generalist or specialist positioning).

To determine and/or examine overall behaviour of simulation models with large input using as few parameters as possible. To introduce a methodology describing stability of the partitioning of simulation results and the corresponding parameter space.

Partitionings of the parameter space are performed using real‐valued mappings called measures of merit. Tools for examining evolution of partitionings and correlations between different partitionings are developed. These tools are applied in two case studies within the field of electrical engineering.

The presented approach provides tools for systematic analysis of parametrised models. Since the classification of results is based on measures of merit, a good choice both simplifies the analysis and improves the stability of partitioning. Included case studies highlight these conclusions.

The present form of the methodology is targeted at recursive simulations. Use of more complex partitioning procedures could be the topic of further research.

Solid framework for handling and analysing complex parametrised simulations.

During the last ten years, the number of research‐level serials has grown rapidly, and serials costs have increased at an even faster rate. These events, coupled with other inflationary pressures and nearly static or declining budgets, forced academic research libraries to shift collections‐funding patterns significantly. As a result, they repeatedly reduced their support of monograph‐rich collections in order to pay for a series of unexpectedly large cost increases in serial‐rich collections. Despite such stopgap fund transfers, serials costs often outstripped their increased allotments. Cancellation of serial acquisitions, serials ordering moratoria, buy‐one‐cancel‐one policies, and other assorted roadblocks or holding actions frequently resulted in a qualitative decline in serial‐rich collections, yet seldom prevented the publication of new serials or the continued increases in prices. Acknowledging the notoriety of this problem among research librarians, I call it “the serials problem.”

This paper aims to examine the antecedent of purchase intention: online seller reputation, product category and surcharge.

This paper uses five experimental designs to explore the seller reputation, product category and surcharge effects in Internet shopping. The authors chose one seller of low reputation and one seller of high reputation from Yahoo Mall. ANOVA are used to evaluate the results.

Sellers of high reputation can post higher surcharges to increase the total price paid by the buyer, but sellers of low reputation cannot do so (experiment 1). Moreover, partitioned price will decrease purchase intention for sellers of low reputation more than for sellers of high reputation (experiment 2). Consumers take the longest time to make purchasing decisions when buying credence goods (experiment 3) or buying from sellers of low reputation (experiment 4). The effect of surcharge levied by sellers of low reputation is weakened for consumers with low (vs high) shipping‐charge skepticism (experiment 5).

This study is helpful to online sellers if they can identify their reputation, product category and those consumers who have shipping‐charge skepticism, they can create extra profit through surcharge practice.

The authors’ investigation extends the literature on consumers’ price processing by identifying the important moderators (seller reputation, product category, and elaboration) and probing into the decision process (via the response time). The results suggest prescriptive strategies for online sellers.

Scheduling in information-driven design phase of construction projects is challenging due to multiple entity types (teams, components, deliverables, activities or parameters) and their dependencies/linkages. Established techniques such as dependency structure matrix (DSM), beeline diagramming method (BDM), multiple domain matrix (MDM), etc. have been independently utilized in past to model information dependencies/linkages and associated iteration. However, there has not been a holistic solution yet for scheduling multiple entity types and their relationships. Hence, an integrated solution needs to be developed that schedules information-driven projects accurately.

A case study data collection approach is utilized. With data from two projects, i.e. hostel design and highway design, a BDM–MDM integrated solution was developed and applied to the same. Feedback from experts was obtained for refinements.

The proposed solution is efficient for scheduling multiple entity types and their information dependencies/linkages.

The proposed integrated solution enables the project participants to schedule information-driven projects systematically. Application to two distinct design cases emphasizes that the concept is generic and can be applied to any information-driven project with multiple entity types.

The BDM–MDM integrated solution concept is investigated for scheduling multiple entity types in any information-driven projects. This study also explored the terminologies such as multiple entity types and information-driven scheduling.

The COVID-19 outbreak disrupted the business environment and severely affected the morale and performance of the employees. Further, the Indian automobile industry witnessed major setbacks and drastically impacted sector in COVID-19. Talent agility is an emerging concept in the field of HRM that will foster innovations and productivity in the automobile industry. Thus, this study aims to explore the barriers to building in-house agile talents in the Indian automobile industry in the new normal.

The barriers of talent agility were identified through a literature review and validated through experts’ opinions. This study used a hybrid approach, which combines Interpretive Structural Modelling-Polarity (ISM-P) and decision-making trial and evaluation laboratory (DEMATEL) to develop a hierarchical structural model of the barriers, followed by classification into cause and effect groups.

The result of the multi-method approach identified that shortage of skills and competencies, lack of IT infrastructure, lack of ambidextrous leaders, lack of smart HRM technologies and practices, lack of attractive reward system/career management, poor advanced T&D, poor industry, institute interface and financial constraints are the critical barriers.

It can provide a strategic roadmap for automobile manufacturers to promote talent agility in the current wave of digitalization (Industry 4.0). This study can help the managers to address and overcome the barrier and hurdles in building talent agility.

This study is unique in that it addresses the contemporary issues related to talent agility in the context of the Indian automobile industry in the current rapidly changing environment. This study developed a holistic integrated ISM(P)-DEMATEL hierarchical framework on the barriers of talent agility indicating inner dependency weights, i.e., the strength of interrelationship between the barriers.

The purpose of this paper is to describe a segmentation technique based on geostatistical modeling methods utilizing geographically weighted regression (GWR) to identify submarkets which could be applied within the mass appraisal environment.

Given the spatial dimension within which neighbourhoods/submarkets exist, this paper has sought to utilize the geostatistical technique of GWR to identify them.

The efficacy of the procedure is established by demonstrating improvements in predictive accuracy of the resultant segmented market models as compared to a baseline global unsegmented model for each of the study areas. Optimal number of segments is obtained by measures of predictive accuracy, spatial autocorrelation in the residual errors and the Akaike information criterion.

The three datasets used allowed for an evaluation of the robustness of the method. Nonetheless it would be beneficial to test it on other datasets, particularly from different regions of the world.

Many researchers and mass appraisal practitioners have established the benefit of segmenting a study area into two or more submarkets as a means of incorporating the effects of location within mass valuation models. This approach develops the existing knowledge.

The research ultimately is developing more accurate valuation models upon which the property tax is based. This should create an environment of fair and acceptable assessed values by the tax paying community.

The contribution of this work lies in the methodological approach adopted which incorporates a market basket approach developed through a process of GWR. The importance of the research findings illustrate that submarket segmentation need no longer be an arbitrary process.

This paper aims to estimate the determinants of the intensity of use of financial inclusion by households in Ghana.

Due to the reality of a household using one or more financial products or services, this study uses the generalised Poisson model applied to GLSS6 and GLSS7 data collected in 2012/2013 and 2016/2017 respectively, to estimate the determinants of the intensity of use of financial inclusion. To deepen the analysis, a multinomial probit model is also applied.

Results show that infrastructural variables such as roads, public transport and banks stimulate the intensity of financial inclusion. In addition, agricultural development characteristics such as markets and cooperatives are essential for the intensity of inclusion.

There is a need to incorporate how many services or depth of services that people use as part of the conceptualisation of financial inclusion, as this can provide more policy-relevant evidence to enhance priority setting in financial inclusion policies. Also, micro-level financial inclusion studies in agrarian economies should consider exploring agricultural development and infrastructure variables in the modelling framework. As lead to further studies, count models of financial inclusion should consider exploring cross-country analysis, the use of panel data, or other methodological approaches to provide more robust evidence.

Previous studies have not modelled financial inclusion based on a count model as a means of measuring intensity though conceptualisations highlight the fact that people use varied financial products or services. Following from this angle, to the best of the authors’ knowledge, this study provides the first attempt at analysing the underlying determinants of the number of financial products or services used by households.