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Conventional tests of the regression discontinuity design’s identifying restrictions can perform poorly when the running variable is discrete. This paper proposes a test for manipulation of the running variable that is consistent when the running variable is discrete. The test exploits the fact that if the discrete running variable’s probability mass function satisfies a certain smoothness condition, then the observed frequency at the threshold has a known conditional distribution. The proposed test is applied to vote tally distributions in union representation elections and reveals evidence of manipulation in close elections that is in favor of employers when Republicans control the NLRB and in favor of unions otherwise.

Information and communications technology (ICT) offers enormous opportunities for individuals, businesses and society. The application of ICT is equally important to economic and non-economic activities. Researchers have increasingly focused on the adoption and use of ICT by small and medium enterprises (SMEs) as the economic development of a country is largely dependent on them. Following the success of ICT utilisation in SMEs in developed countries, many developing countries are looking to utilise the potential of the technology to develop SMEs. Past studies have shown that the contribution of ICT to the performance of SMEs is not clear and certain. Thus, it is crucial to determine the effectiveness of ICT in generating firm performance since this has implications for SMEs’ expenditure on the technology. This research examines the diffusion of ICT among SMEs with respect to the typical stages from innovation adoption to post-adoption, by analysing the actual usage of ICT and value creation. The mediating effects of integration and utilisation on SME performance are also studied. Grounded in the innovation diffusion literature, institutional theory and resource-based theory, this study has developed a comprehensive integrated research model focused on the research objectives. Following a positivist research paradigm, this study employs a mixed-method research approach. A preliminary conceptual framework is developed through an extensive literature review and is refined by results from an in-depth field study. During the field study, a total of 11 SME owners or decision-makers were interviewed. The recorded interviews were transcribed and analysed using NVivo 10 to refine the model to develop the research hypotheses. The final research model is composed of 30 first-order and five higher-order constructs which involve both reflective and formative measures. Partial least squares-based structural equation modelling (PLS-SEM) is employed to test the theoretical model with a cross-sectional data set of 282 SMEs in Bangladesh. Survey data were collected using a structured questionnaire issued to SMEs selected by applying a stratified random sampling technique. The structural equation modelling utilises a two-step procedure of data analysis. Prior to estimating the structural model, the measurement model is examined for construct validity of the study variables (i.e. convergent and discriminant validity).

The estimates show cognitive evaluation as an important antecedent for expectation which is shaped primarily by the entrepreneurs’ beliefs (perception) and also influenced by the owners’ innovativeness and culture. Culture further influences expectation. The study finds that facilitating condition, environmental pressure and country readiness are important antecedents of expectation and ICT use. The results also reveal that integration and the degree of ICT utilisation significantly affect SMEs’ performance. Surprisingly, the findings do not reveal any significant impact of ICT usage on performance which apparently suggests the possibility of the ICT productivity paradox. However, the analysis finally proves the non-existence of the paradox by demonstrating the mediating role of ICT integration and degree of utilisation explain the influence of information technology (IT) usage on firm performance which is consistent with the resource-based theory. The results suggest that the use of ICT can enhance SMEs’ performance if the technology is integrated and properly utilised. SME owners or managers, interested stakeholders and policy makers may follow the study’s outcomes and focus on ICT integration and degree of utilisation with a view to attaining superior organisational performance.

This study urges concerned business enterprises and government to look at the environmental and cultural factors with a view to achieving ICT usage success in terms of enhanced firm performance. In particular, improving organisational practices and procedures by eliminating the traditional power distance inside organisations and implementing necessary rules and regulations are important actions for managing environmental and cultural uncertainties. The application of a Bengali user interface may help to ensure the productivity of ICT use by SMEs in Bangladesh. Establishing a favourable national technology infrastructure and legal environment may contribute positively to improving the overall situation. This study also suggests some changes and modifications in the country’s existing policies and strategies. The government and policy makers should undertake mass promotional programs to disseminate information about the various uses of computers and their contribution in developing better organisational performance. Organising specialised training programs for SME capacity building may succeed in attaining the motivation for SMEs to use ICT. Ensuring easy access to the technology by providing loans, grants and subsidies is important. Various stakeholders, partners and related organisations should come forward to support government policies and priorities in order to ensure the productive use of ICT among SMEs which finally will help to foster Bangladesh’s economic development.

This chapter introduces four research methods that are not covered in the previous chapters. They are (1) non-parametric statistics, (2) interpretive structural modeling, (3) analytic hierarchy process, and (4) data envelopment analysis. The methods are discussed with examples. The discussion, however, is introductory; so we urge the reader to go through the pertinent references for details.

The purposes of this research are to study the theory and method of multi-attribute index system design and establish a set of systematic, standardized, scientific index systems for the design optimization and inspection process. The research may form the basis for a rational, comprehensive evaluation and provide the most effective way of improving the quality of management decision-making. It is of practical significance to improve the rationality and reliability of the index system and provide standardized, scientific reference standards and theoretical guidance for the design and construction of the index system.

Using modern methods such as complex networks and machine learning, a system for the quality diagnosis of index data and the classification and stratification of index systems is designed. This guarantees the quality of the index data, realizes the scientific classification and stratification of the index system, reduces the subjectivity and randomness of the design of the index system, enhances its objectivity and rationality and lays a solid foundation for the optimal design of the index system.

Based on the ideas of statistics, system theory, machine learning and data mining, the focus in the present research is on “data quality diagnosis” and “index classification and stratification” and clarifying the classification standards and data quality characteristics of index data; a data-quality diagnosis system of “data review – data cleaning – data conversion – data inspection” is established. Using a decision tree, explanatory structural model, cluster analysis, K-means clustering and other methods, classification and hierarchical method system of indicators is designed to reduce the redundancy of indicator data and improve the quality of the data used. Finally, the scientific and standardized classification and hierarchical design of the index system can be realized.

The innovative contributions and research value of the paper are reflected in three aspects. First, a method system for index data quality diagnosis is designed, and multi-source data fusion technology is adopted to ensure the quality of multi-source, heterogeneous and mixed-frequency data of the index system. The second is to design a systematic quality-inspection process for missing data based on the systematic thinking of the whole and the individual. Aiming at the accuracy, reliability, and feasibility of the patched data, a quality-inspection method of patched data based on inversion thought and a unified representation method of data fusion based on a tensor model are proposed. The third is to use the modern method of unsupervised learning to classify and stratify the index system, which reduces the subjectivity and randomness of the design of the index system and enhances its objectivity and rationality.

The purpose of this paper is to consider the general k level step-stress accelerated life test with the Rayleigh lifetime distribution for units subjected to stress under progressive Type-I censoring.

The parameter of this distribution is assumed to be a log-linear function of the stress, and a tampered failure rate model holds. The progressive Type-I censoring reduces the cost of testing. Due to constrained resources in practice, the test design must be optimized carefully. A numerical study is conducted to illustrate the optimum test design based on several four optimality criteria under the constraint that the total experimental cost does not exceed a pre-specified budget.

This paper compares unconstrained and constrained optimal k level step-stress test. Based on the results of the simulation study, the cost constraint reduces cost and time of the test and it also, in the most cases, increases the efficiency of the test. Also, the T-optimal design is lowest cost and time for testing and it is found more optimal in both conditions.

In this paper, various optimization criteria for selecting the stress durations have been used, and these criteria are compared together. Also, because of affecting the stress durations on the experimental cost, the author optimize under the constraint that the total experimental cost does not exceed a pre-specified budget. The efficiency of the unconstrained test in comparison with constrained test is discussed.

Unfortunately, the occurrence of natural disasters is inevitable all over the world. Hence, this paper aims to analyze a scenario-based collaborative problem in a relief supply chain (RSC), where nongovernmental organizations can participate in relief activities with governmental organizations. This study focuses on location-allocation, inventory management and distribution planning under uncertain demand, budget, transportation and holding costs where government and private distribution centers receive relief items from suppliers then send them to affected areas. The performance of the proposed model is surveyed in a real case study in Dorud.

This paper develops a nonlinear mixed-integer programming model that seeks to maximize the coverage of demand points and minimize operating costs and traveled distance. The linear programming-metric technique and grasshopper optimization algorithm are applied to survey the model's applicability and efficiency.

This study compares noncollaborative and collaborative cases in terms of the number of applied distribution centers and RSC's goals, then demonstrates that the collaborative model not only improves the coverage of demand points but also minimizes cost and traveled distance. In fact, the presented approach helps governments efficiently surmount problems created after a disaster, notwithstanding existing uncertainties, by determining a strategic plan for collaboration with nongovernmental organizations for relief activities.

Relief strategies considered in previous research have not been sufficiently examined from the perspective of collaboration of governmental and nongovernmental organizations and provided an approach to develop the coverage of affected areas and reducing costs and traveled distance despite various uncertainties. Hence, the authors aim to manage RSCs better by offering a mathematical model whose performance has been proved in a real case study.

The purpose of this paper is to know whether the authors’ productivity pattern of library and information science (LIS) open access journals adheres to Lotka’s inverse square law of scientific productivity. Since the law was introduced, it has been tested in various fields of knowledge, and results have varied. This study has closely followed Lotka’s inverse square law in the field of LIS open access journals to find a factual result and set a baseline for future studies on author productivity of LIS open access journals.

The publication data of selected ten LIS open access journals pertain to authorship, citations were downloaded from the Scopus database and analysed using bibliometric indicators like authorship pattern, collaborative index (CI), degree of collaboration (DC), collaborative coefficient (CC) and citation counts. This study has applied Lotka’s inverse square law to assess authors’ productivity pattern of LIS open access journals and further Kolmogorov-Smirnov (K-S) goodness-of-fit test applied for testing of observed and expected author productivity data.

Inferences were drawn for the set objectives on authorship pattern, collaboration trend and authors’ productivity pattern of LIS open access journals covered in this study. The single authorship pattern is dominant in LIS open access journals covered in this study. The CI, DC and CC are found to be 1.95, 0.47 and 0.29, respectively. The expected values as per Lotka’s law (n = −2) significantly vary from the observed values as per the chi-square test and K-S goodness-of-fit test. Hence, this study does not adhere to Lotka’s inverse square law of scientific productivity.

Researchers may find an idea about the authors’ productivity patterns of LIS open access journals. This study has used the K-S goodness-of-fit test and the chi-square test to validate the authors’ productivity data. The inferences found out from this study will be a baseline for future research on author productivity of LIS open access journals.

This study is significant from the viewpoint of the growing research on open access journals in the field of LIS and to identify the authorship pattern, collaboration trend and author productivity pattern of such journals.

The internal factors that influence the decision to change dividend growth rates include two competing models: the earnings and free cash flow models. As far as each of the components of each model is considered, the informative and efficient dividend payout decisions require that managers have to focus on the significant component(s) only. This study examines the cointegration, significance, and explanatory power of those components empirically. The expected outcomes serve two objectives. First, on an academic level, it is interesting to examine the extent to which payout practices meet the premises of the earnings and free cash flow models. The latter considers dividends and financing decisions as two faces of the same coin. Second, on a professional level, the outcomes help focus the management’s efforts on the activities that can be performed when considering a change in dividend growth rates.

This study uses data for the firms listed in two indexes: Dow Jones Industrial Average (DJIA30) and NASDAQ100. The data cover quarterly periods from 30 June 1989 to 31 March 2011. The methodology includes (a) cointegration analysis in order to test for model specification and (b) classical regression in order to examine the explanatory power of the components of earnings and free cash flow models.

The results conclude that: (a) Dividends growth rates are cointegrated with the two models significantly; (b) Dividend growth rates are significantly and positively associated with growth in sales and cost of goods sold only. Accordingly, these are the two activities that firms’ management need to focus on when considering a decision to change dividend growth rates, (c) The components of the earnings and free cash flow models explain very little of the variations in dividends growth rates. The results are to be considered a call for further research on the external (market-level) determinants that explain the variations in dividends growth rates. Forthcoming research must separate the effects of firm-level and market-level in order to reach clear judgments on the determinants of dividends growth rates.

This study contributes to the related literature in terms of offering updated robust empirical evidence that the decision to change dividend growth rate is discretionary to a large extent. That is, dividend decisions do not match the propositions of the earnings and free cash flow models entirely. In addition, the results offer solid evidence that financing trends in the period 1989–2011 showed heavy dependence on debt financing compared to other related studies that showed heavy dependence on equity financing during the previous period 1974–1984.

The purpose of this paper is to propose a system with the highest discriminatory power by selecting an indicator system based on the K–S test according to the unique circumstances of small enterprises.

The proposed method relies on calculating the K–S test statistical magnitude of D iteratively to reach a system with the maximum discriminatory power.

The empirical results, demonstrated using 3,045 small businesses from a Chinese bank, show that credit rating system should focus on the indicator system’s discriminatory power rather than a single indicator’s discriminatory power, because the interaction between indicators affects the discriminatory power of the system.

The proposed method creates a credit rating system with the highest discriminatory power, rather than its indicators, which is a more reasonable and novel approach to credit rating.

The approach is unique because the final system will have high discriminatory power and has excellent potential for decision support. The authors believe that this contribution is theoretically and practically relevant because credit rating for small business is especially difficult and complicated.