Emotion and interior space design: an ergonomic perspective

Interaction between the users and their environment is spontaneous and unavoidable. This interaction can be positive or negative. A good interior space is about considering all the physical, environmental and cognitive elements and harmonizing them to make it a space that feels right, functionally and emotionally. The important element that has to be considered the most in an interior space is the "user". Balancing all these elements is a challenging job and results in a perfect interior space design. This paper intends to bring to light the necessity of designing an optimum interior space, which is a balance of the user's choice and the mandatory standards that ought to be followed for user safety and convenience. There has to be an intervening domain of ergonomics which will guide to bring out a balance between the personal choice of the user and the usual standards followed. It should also provide a step-by-step information, guidance and direction to act to the specifications and standards systematically to adapt an integrated approach of handling all the elements holistically which will indeed result in a good interior space.     

Fluidity amidst structure: multi-racial identity constructions across the life course of Malaysians and Singaporeans

ABSTRACT

Multi-racial identity construction is understood to be fluid, contextual and dynamic. Yet the dynamics of multi-racial identity construction when racial identities are ascribed and formulated as static by governments is less explored in psychological studies of race. This paper examines the dynamics of racial identity construction among multi-racial Malaysians and Singaporeans in a qualitative study of 31 semi-structured interviews. Thematic analysis was used to identify the different private racial identity constructions of participants who were officially ascribed with single racial identities at birth. Participants reflected on the overwhelming influence of the state and significant Others in limiting their ability to express their multiple racial identities when they were in school, and highlighted their capacity to be agentic in their private racial identity constructions when they were older. This paper shows that across the life course multi-racial individuals possess (1) the ability to adopt different racial identity positions at different times, (2) the ability to hold multiple racial identity constructions at the same time when encounters with Others are dialogical, (3) the reflexivity of past identity positions in the present construction of identities.     

Industrial welfare and the state: nation and city reconsidered

Industrial welfare history presents important challenges to developmental state theories in “late” industrialization. This article expands the debate by examining how nation-states create statutory welfare by addressing institutional variety beyond markets. It is simplistic to argue linear growth of national welfare or of states autonomously regulating markets to achieve risk-mitigation. I contend that welfare institutions emerge from the state’s essential conflict and collaboration with various alternate institutions in cities and regions. Using histories of Europe, India, and Karnataka, I propose a place-based, work-based, and work-place based welfare typology evolving at differential rates. Although economic imperatives exist to expand local risk-pools, it is precisely the alternate institutional diversity that makes late industrial nation-states unable or unwilling to do so. This results in institutionally “thin,” top-down industrial welfare. Ultimately, theories that overly depend on histories of small nations, homogenous nations, or city-states, provide weak tests of the economics of industrial welfare.     

Extension of the Application of Conway‐Maxwell‐Poisson Models: Analyzing Traffic Crash Data Exhibiting Underdispersion

The objective of this article is to evaluate the performance of the COM‐Poisson GLM for analyzing crash data exhibiting underdispersion (when conditional on the mean). The COM‐Poisson distribution, originally developed in 1962, has recently been reintroduced by statisticians for analyzing count data subjected to either over‐ or underdispersion. Over the last year, the COM‐Poisson GLM has been evaluated in the context of crash data analysis and it has been shown that the model performs as well as the Poisson‐gamma model for crash data exhibiting overdispersion. To accomplish the objective of this study, several COM‐Poisson models were estimated using crash data collected at 162 railway‐highway crossings in South Korea between 1998 and 2002. This data set has been shown to exhibit underdispersion when models linking crash data to various explanatory variables are estimated. The modeling results were compared to those produced from the Poisson and gamma probability models documented in a previous published study. The results of this research show that the COM‐Poisson GLM can handle crash data when the modeling output shows signs of underdispersion. Finally, they also show that the model proposed in this study provides better statistical performance than the gamma probability and the traditional Poisson models, at least for this data set.     

Teaching Three Year-Olds to Pass False Belief Tests: A Conversational Approach

A training procedure was developed for teaching three year-old children to pass a standard false belief task. A series of 4 video sequences was developed, in each of which a child showed surprise following the unexpected transfer of an object. A group of 23 three year-olds who failed a standard false belief task took part in 8 discussions of the 4 video clips, over a period of two weeks, and were compared with a control group of 23 task-failers who had 8 story reading sessions over the same time period. The training involved (a) interactive recall of the initial events in each sequence, (b) factual questioning about the events and (c) an explanation of the thoughts and actions of the video protagonists. The emphasis was on positive elaboration of children's answers rather than on negative feedback as counter evidence. The training group performed significantly better at an immediate post-test, and at a follow-up test two weeks later, on a similar as well as a generalisation task. Task success was unrelated to vocabulary (BPVS) score, but was significantly related to success of responses during the training. The results indicate learning in the Training group of a discursive format for talking about events useful for describing false beliefs.     

Application of the Hyper‐Poisson Generalized Linear Model for Analyzing Motor Vehicle Crashes

The hyper‐Poisson distribution can handle both over‐ and underdispersion, and its generalized linear model formulation allows the dispersion of the distribution to be observation‐specific and dependent on model covariates. This study's objective is to examine the potential applicability of a newly proposed generalized linear model framework for the hyper‐Poisson distribution in analyzing motor vehicle crash count data. The hyper‐Poisson generalized linear model was first fitted to intersection crash data from Toronto, characterized by overdispersion, and then to crash data from railway‐highway crossings in Korea, characterized by underdispersion. The results of this study are promising. When fitted to the Toronto data set, the goodness‐of‐fit measures indicated that the hyper‐Poisson model with a variable dispersion parameter provided a statistical fit as good as the traditional negative binomial model. The hyper‐Poisson model was also successful in handling the underdispersed data from Korea; the model performed as well as the gamma probability model and the Conway‐Maxwell‐Poisson model previously developed for the same data set. The advantages of the hyper‐Poisson model studied in this article are noteworthy. Unlike the negative binomial model, which has difficulties in handling underdispersed data, the hyper‐Poisson model can handle both over‐ and underdispersed crash data. Although not a major issue for the Conway‐Maxwell‐Poisson model, the effect of each variable on the expected mean of crashes is easily interpretable in the case of this new model.     

Determinants of Interoutsourcing: An Analytical Approach

Interoutsourcing is a round‐way process in which the vendor is its customer's customer and the customer is its vendor's vendor. While interoutsourcing is emerging as a prominent outsourcing strategy in many industries, there are no rigorous analytical studies focusing on this mechanism. In this article, we analytically demonstrate the efficacy of interoutsourcing by comparing it with normal outsourcing. Our results show that, compared with normal outsourcing, interoutsourcing acts as a self‐enforcer of vendor firms' behaviors toward increasing outsourcing service value. However, in situations where there is a mismatch of outsourcing activities, a high degree of incentive that is based on outsourcing service value, and a high cost of capital, interoutsourcing is not preferred to normal outsourcing. We discuss these results in detail and provide managerial implications for firms involved in interoutsourcing decisions.     

Efficient formation of storage classes for warehouse storage location assignment: A simulated annealing approach

Class-based storage policy distributes products among a number of classes and for each class it reserves a region within the storage area. The procedures reported in the literature for formation of storage classes primarily consider order-picking cost ignoring storage-space cost. Moreover, in these procedures items are ordered on the basis of their cube per order index (COI), and items are then partitioned into classes maintaining this ordering. This excludes many possible product combinations in forming classes which may result in inferior solutions. In this paper, a simulated annealing algorithm (SAA) is developed to solve an integer programming model for class formation and storage assignment that considers all possible product combinations, storage-space cost and order-picking cost. Computational experience on randomly generated data sets and an industrial case shows that SAA gives superior results than the benchmark dynamic programming algorithm for class formation with COI ordering restriction.