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Orienting parts that measure only a few micrometers in diameter introduces several challenges that need not be considered at the macro‐scale. First, there are several kinds of sticking effects due to Van der Waals forces and static electricity, which complicate hand‐off motions and release of a part. Second, the degrees of freedom of micro‐manipulators are limited. This paper proposes a pair of manipulation primitives and a complete algorithm that addresses these challenges. We will show that a sequence of these two manipulation primitives can uniquely orient any asymmetric part while maintaining contact without sensing. This allows us to apply the same plan to many (identical) parts simultaneously. For asymmetric parts we can find a plan of length O(n) in O(n) time that orients the part, where n is the number of vertices.

This chapter describes and tests the principles of configural theory in the context of hospitality frontline service employees’ happiness-at-work and managers’ assessments of these employees’ quality of work performances. The study proposes and tests empirically a configural asymmetric theory of the antecedents to hospitality employee happiness-at-work and managers’ assessments of employees’ quality of work performance. The findings confirm and go beyond prior statistical findings of small-to-medium effect sizes of happiness-performance relationships. The method includes matching cases of data from surveys of employees (n = 247) and surveys completed by their managers (n = 43) and uses qualitative comparative analysis via the software program fsQCA.com. The findings support the four principles of configural analysis and theory construction: recognize equifinality of different solutions for the same outcome; test for asymmetric solutions; test for causal asymmetric outcomes for very high versus very low happiness and work performance; and embrace complexity. The theory and findings confirm that configural theory and research resolves perplexing happiness–performance conundrums. The study provides algorithms involving employees’ demographic characteristics and their assessments of work facet-specifics which are useful for explaining very high happiness-at-work and high quality-of-work performance (as assessed by managers) – as well as algorithms explaining very low happiness and very low quality-of-work performance.

This study applies asymmetric rather than conventional symmetric analysis to advance theory in occupational psychology. The study applies systematic case-based analyses to model complex relations among conditions (i.e., configurations of high and low scores for variables) in terms of set memberships of managers. The study uses Boolean algebra to identify configurations (i.e., recipes) reflecting complex conditions sufficient for the occurrence of outcomes of interest (e.g., high versus low financial job stress, job strain, and job satisfaction). The study applies complexity theory tenets to offer a nuanced perspective concerning the occurrence of contrarian cases – for example, in identifying different cases (e.g., managers) with high membership scores in a variable (e.g., core self-evaluation) who have low job satisfaction scores and when different cases with low membership scores in the same variable have high job satisfaction. In a large-scale empirical study of managers (n = 928) in four (contextual) segments of the farm industry in New Zealand, this study tests the fit and predictive validities of set membership configurations for simple and complex antecedent conditions that indicate high/low core self-evaluations, job stress, and high/low job satisfaction. The findings support the conclusion that complexity theory in combination with configural analysis offers useful insights for explaining nuances in the causes and outcomes to high stress as well as low stress among farm managers. Some findings support and some are contrary to symmetric relationship findings (i.e., highly significant correlations that support main effect hypotheses).

Because of Southeast Asia's strong economic performance in the past decade and great marketing potential, many Western marketers have increased their marketing activities in this area and hope for a lucrative future. Along with this strong marketing interest is a rapid increase in the number of Western advertising agencies and advertising expenditures in Southeast Asia. For example, six out of the top ten agencies in Taiwan are managed by, or work in cooperation with, American or Japanese agencies (Taipei Advertising Agency Association, 1992). According to Ogilvy & Mather, in 1985, advertising expenditures in Southeast Asia rose by almost 50 percent from 1980 to 1984. During this period, over one billion dollars were spent on mass media advertising in the region (Frith & Frith, 1990). And for the first time, U.S. agency billings from foreign sources surpassed domestic billings in 1988 (Frazer, 1990). International advertising has become a big business in Southeast Asia.

This paper aims to verify the workspace and movement performance of a redundantly actuated humanoid chewing robot.

A redundantly actuated humanoid chewing robot with 6-PUS linkages and two higher kinematic pairs (HKPs) is introduced. The design of HKPs is specified by mimicking the temporomandibular joint (TMJ) structure obtained through a computed tomography scan of the mastication system. The border movement, mouth-opening trajectory and velocity of subjects’ lower incisor point are measured by using the mandibular kinesiograph. Based on the kinematics, the envelope of the workspace is analyzed. The workspace and mouth-opening movement experiments are carried out. The border movement of the lower incisor point is measured. The mouth-opening trajectory is planned and tested on the chewing robot.

Comparing with measurement results of border movement and mouth-opening movement of human, it is shown that the humanoid chewing robot can meet the workspace requirements and is able to perform mouth-opening movement like human-beings.

The chewing robot is designed to reproduce human jaw movements and application in test of dental components and materials or evaluation of food textural properties.

The chewing robot is inspired by the mastication system which itself is mechanically redundant because of the TMJ and more muscles than required. The novel spatial redundantly actuated chewing robot is the first of this kind with two HKPs to mimic the human TMJ and is a higher fidelity mechanism.

This chapter identifies research advances in theory and analytics that contribute successfully to the primary need to be filled to achieve scientific legitimacy: configurations that include accurate explanation, description, and prediction – prediction here refers to predicting future outcomes and outcomes of cases in samples separate from the samples of cases used to construct models. The MAJOR PARADOX: can the researcher construct models that achieve accurate prediction of outcomes for individual cases that also are generalizable across all the cases in the sample? This chapter presents a way forward for solving the major paradox. The solution here includes philosophical, theoretical, and operational shifts away from variable-based modeling and null hypothesis statistical testing (NHST) to case-based modeling and somewhat precise outcome testing (SPOT). These shifts are now occurring in the scholarly business-to-business literature.

How an individual makes a travel decision under uncertain conditions has been one of the critical issues in designing the information that is delivered by Intelligent Transportation Systems (ITS). This has been a difficult problem because a suitable mathematical framework that deals with the interaction among uncertainty, information, and traveler's attitude toward uncertainty is not available. This paper introduces a possibility theory framework, and demonstrates how this framework represents the uncertainty perceived by the traveler, and calculates the feasibility of achieving the travel objective under different degrees of specificity of information. We present this framework in the setting of selecting the time of departure in the face of a not well-defined desired arrival time and estimated travel time. Feasibility of arrival is measured by the possibility and necessity measures; these measures represent two views, optimistic or conservative, respectively. Anxiety that is associated with the departure time, whether to leave now or not is modeled by Yager's anxiety measures. The anxiety measure considers the conflict of impelling forces between “to leave now” and “not to leave yet”; possibility and necessity measures for these outcomes represent these forces. Thus, along the time axis of possible departure time, possibility and necessity measures of arrival and non-arrival are computed and accordingly, the anxiety measure associated with each departure time. The range of time within which a traveler decides to leave is indicated by the anxiety measure. The size of the range is sensitive to the specificity of information. The more specific the information, the smaller the range of time. While the purpose of this paper is to introduce the mathematical framework useful for the analysis of a traveler's decision under uncertainty, the analysis raises an interesting issue of the paradoxical effects of information accuracy also.

Currently, most of the empirical management, marketing, and psychology articles in the leading journals in these disciplines are examples of bad science practice. Bad science practice includes mismatching case (actor) focused theory and variable-data analysis with null hypothesis significance tests (NHST) of directional predictions (i.e., symmetric models proposing increases in each of several independent X’s associates with increases in a dependent Y). Good science includes matching case-focused theory with case-focused data analytic tools and using somewhat precise outcome tests (SPOT) of asymmetric models. Good science practice achieves requisite variety necessary for deep explanation, description, and accurate prediction. Based on a thorough review of relevant literature, Hubbard (2016) concludes that reporting NHST results (e.g., an observed standardized partial regression betas for X’s differ from zero or that two means differ from zero) are examples of corrupt research. Hubbard (2017) expresses disappointment over the tepid response to his book. The pervasive teaching and use of NHST is one ingredient explaining the indifference, “I can’t change just because it’s [NHST] wrong.” The fear of submission rejection is another reason for rejecting asymmetric modeling and SPOT. Reporting findings from both bad and good science practices may be necessary until asymmetric modeling and SPOT receive wider acceptance than held presently.