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The authors construct two time-varying political connection (PC) indexes to measure a firm's political tendencies toward ruling and opposing parties and analyze whether a firm with ruling party tendencies obtains better bank loan contracts compared to the contracts obtained by a firm with opposing party tendencies and a firm with fixed PC tendencies.

Linguistic text mining is used to construct the two time-varying PC indexes from news sources that reflect the tone and frequencies of characteristic texts to determine a firm's tendencies to favor the ruling or opposing parties.

The results show that varying PC firms connected to the ruling party receive preferential loan contracts when their political tendencies increase but varying PC firms connected to the opposition party do not. In contrast, fixed PC firms gain similar benefits only when the connection is determined in the presidential election year but not in other years. Firms supporting two parties receive minimal financial rewards in terms of loan terms.

In past studies, once a firm is identified as having a connection with a political party, it is assumed to have PC throughout the sample period (i.e. fixed PC firms). The authors lift this assumption and examine how varying PC affect bank loan contracts. The two time-varying PC indexes can identify a firm's more immediate party tendencies and more precise effects of a firm's party tendencies on bank loan contracts.

Southeast Asia has been actively undergoing land conversion into agricultural lands over past few decades. This creates the challenges to the nation in dealing with the non-point source pollutants in many fluvial systems, thus requiring an effective approach in sediment source apportionment for an appropriate target mitigation procedure. The trace element property from different source points was used for catchment classification of Galas River. Sediment sample collection was carried out at the sources and sink areas of the catchment system. Fine sediment was analysed using X-ray fluorescence to obtain elemental composition followed by the statistical test and numerical model. Out of 83 elements, 12 elements (Mn, Ca, Cr, Ga, Dy Hf, Y, V, Th, Pb, Zn and Sr) have been selected as best tracer signatures. The solver model has indicated Pergau River as the major sediment contributor to this large catchment system. The model output could directly be proportional with the land-use practice, indicating excessive terrestrial alteration has taken place within the sites for agricultural plantation purposes. Thus, this highly recommends for the decision-making use to the targeted areas to overcome the serious sedimentation issues caused by the tillage operation in affected stream points and to improve the watershed quality.

This paper aims to provide a review of different types of non-wearable human identification sensors which can be applied for smart home environment.

The authors performed a systematic review to assess and compare different types of non-wearable and non-intrusive human identification sensors used in smart home environment. The literature research adds up to 5,567 records from 2000 to 2016, out of which 40 articles were screened and selected for this review.

In this review, the authors classified non-wearable human identification technologies into four main groups, namely, object-based, footstep-based, body shape-based and gait-based identification technologies. Assessing these four group of identification technologies showed that the maturity of non-wearable identification is not high and most of these technologies are verified in a lab environment. Additionally, footstep-based identification is the most popular identification approach listed in the literature.

This study contributes to the literature on human identification technologies in several ways. This paper identifies the state-of-the-art regarding non-wearable technologies which can be used in smart home environment. Moreover, the results of this paper can provide a better understanding of advantages and disadvantages of the non-wearable identification technologies.

To remanufacture a disused part, a hybrid process needs to be taken in part production. Therefore, a reasonable machining route is necessary to be developed for the hybrid process. This paper aims to develop a novel process planning algorithm for additive and subtractive manufacturing (ASM) system to achieve this purpose.

First, a skeleton of the model is generated by using thinning algorithm. Then, the skeleton tree is constructed based on topological structure and shape feature. Further, a feature matching algorithm is developed for recognizing the different features between the initial model and the final model based on the skeleton tree. Finally, a reasonable hybrid machining route of the ASM system is generated in consideration of the machining method of each different sub-feature.

This paper proposes a hybrid process planning algorithm for the ASM system. Further, it generates new process planning insights on the hybrid process service provider market.

The proposed process planning algorithm enables engineers to obtain a proper hybrid machining route before product fabrication. And thereby, it extends the machining capability of the hybrid process to manufacture some parts accurately and efficiently.

This study addresses one gap in the hybrid process literature. It develops the first hybrid process planning strategy for remanufacturing of disused parts based on skeleton tree matching, which generates a more proper hybrid machining route than the currently available hybrid strategy studies. Also, this study provides technical support for the ASM system to repair damaged parts.

When college entrance examinations act as gatekeepers to modern-sector jobs, the entire education system then becomes oriented toward these examinations. This occurs at the expense of learning for the sake of learning and other aspects of education that address the holistic development and well-being of students. In recent years in China, there has been growing concern that examination competition has compromised the quality of classroom teaching and learning and is detrimental to the development of skills necessary for the global knowledge economy. These concerns have given rise to a far-reaching set of education reforms known as the New Curriculum reforms which have aimed to move students to the center of teaching and learning and to transform teaching and learning so as to foster such capacities as creativity, innovation, collaboration, self-expression, engagement, enjoyment of learning, inquiry skills, problem-solving abilities, and ability to apply knowledge in practice. In this chapter, we use videotaped high school New Curriculum demonstration lessons to examine teaching and learning practices that are regarded as exemplary in the current reform context. We investigate how teachers are negotiating the competing demands of preparing students for the examinations and addressing the aims of the New Curriculum reforms. The nature of student participation in the classroom emerges in the analysis as a key indicator of the success of this negotiation.

The present study attempts to shed some light on tourists’ destination brand loyalty (DBL) in the Malaysian ecotourism context. More specifically, this study aims to examine the relationships between electronic word of mouth (eWOM), destination brand quality (DBQ), destination brand image (DBI), psychological engagement (PE) and DBL.

Based on the Stimulus–Organism–Response theory and buyer black box model, this study developed a framework to address tourists’ loyalty towards ecotourism destinations. An online survey was carried out to collect data, which yielded 210 completed usable responses. Structural equation modelling – partial least squares was used to test the study hypotheses.

Findings from this study revealed that eWOM and destination product quality affect DBI. Moreover, data support the mediating effect of PE between DBI and DBL.

This study provides valuable insights for practitioners and policymakers of the tourism industry in creating a DBI, keeping tourists psychologically engaged and retaining their loyalty to the ecotourism destinations.

This study is amongst the first to examine the effect of eWOM and DBQ on DBI in the ecotourism context. It also examines PE in relation to the DBI, which is a comparatively new area in the literature.

To the authors’ knowledge, this paper is the first to use Detail I/B/E/S to study directly the timeliness of security analysts’ next-year earnings-per-share (EPS) estimates relative to the SEC filings of annual (10-K) and quarterly (10-Q) financial statements. Although the authors do not prove a causal relationship, they provide evidence that the average time from firms’ filings of 10-Ks and 10-Qs to the release of analysts’ annual EPS forecasts during short timeframes (for example, 15-day timeframe from a 10-K’s SEC file date) subsequent to the 10-K and 10-Q filing dates significantly shortened with XBRL implementation and then remained relatively constant following implementation.

Using filing dates hand-collected from the SEC website for 10-Ks during 2009-2011 and filing dates for 10-Ks and 10-Qs during 2003-2014 input from Compustat along with analysts’ estimated values for next year EPS, actual estimated next year EPS realized and estimate announcement dates in Detail I/B/E/S, the authors study the days from 10-K and 10-Q file dates to announcement dates and the per cent errors for individual estimates during per- and post-XBRL eras.

The authors find that analysts are announcing next-year EPS forecasts significantly more frequently and in significantly shorter time in zero to 15 days immediately following 10-K and 10-Q file dates post-XBRL as compared to pre-XBRL. However, the authors do not find a significant change in forecast accuracy post-XBRL as compared to pre-XBRL.

Because this study uses short timeframes immediately following the events (filings of 10-Ks and 10-Qs), the relationship between 10-Ks and 10-Qs with and without XBRL and improved forecast timeliness is strengthened. However, even this strengthened difference-in-difference methodology does not establish causality. Future research may determine whether XBRL or other factors cause the improved forecast timeliness the authors’ evidence.

This improved efficiency may become critical if financial statement reporting expands as a result of new innovations such as Big Data and continuous reporting. In the future, users may be able to electronically connect to financial statement data that firms are maintaining on a perpetual basis on the SEC website and continuously monitor and analyze the financial statement data dynamically in real time. If so, then unquestionably, XBRL will have played a critical role in bringing about this future innovation.

Whereas previous studies have utilized Summary IBES data to assess the impact of XBRL on analyst forecasts, the authors use Detail IBES to study the effects of XBRL adoption directly by measuring days from 10-K and 10-Q file dates in Compustat to each estimate’s announcement date recorded in IBES and by computing the per cent error using each estimate’s VALUE and ACTUAL recorded in Detail IBES. The authors are the first to evidence a significant shortening in average days and an increase in per cent of 30-day counts in the zero- to 15-day timeframe immediately following the fillings of 10-K s and 10-Qs.

It is a challenge to print a model with the size that is larger than the working volume of a three-dimensional (3D) printer. The purpose of this paper is to present a feasible approach to divide a large model into small printing parts to fit the volume of a printer and then assemble these parts into the final model.

The proposed approach is based on the skeletonization and the minima rule. The skeleton of a printing model is first extracted using the mesh contraction and the principal component analysis. The 3D model is then partitioned preliminarily into many smaller parts using the space sweep method and the minima rule. The preliminary partition is finally optimized using the greedy algorithm.

The skeleton of a 3D model can effectively represent a simplified version of the geometry of the 3D model. Using a model’s skeleton to partition the model is an efficient way. As it is generally desirable to have segmentations at concave creases and seams, the cutting position should be located in the concave region. The proposed approach can partition large models effectively to well retain the integrity of meaningful parts.

The proposed approach is new in the rapid prototyping field using the model skeletonization and the minima rule. Based on the authors’ knowledge, there is no method that concerns the integrity of meaningful parts for partitioning. The proposed method can achieve satisfactory results by the integrity of meaningful parts and assemblability for most 3D models.

Additive manufacturing technology significantly simplifies the production of complex three-dimensional (3 D) parts directly from the computer-aided design (CAD) model. Although additive manufacturing (AM) processes have unexampled flexibility, they still have restrictions inhibiting engineers to easily generate some specific geometric shapes, easily. Some of these problems pertain to the consumption of materials as supports, the inferior surface finish of some surfaces with certain angles, etc. One of the approaches to overcome these problems is designing by segmentation.

The proposed methodology consists of two steps: (1) segmentation of the 3 D model and (2) exploring the best orientation for each segment. In the first step, engineers consider the possible number of segments and the connection method of segments. In this paper, a series of segments, called a segmentation pattern (SP), is obtained by the recognition of features and separating them automatically (or manually when needed) with one or more appropriate planes. In the second step, the best fabrication orientation should be chosen. The criteria for choosing the best SP and OPs are minimizing the support volume, building time (directly affected by segments’ height in layer-wise AM processes) and surface roughness. Both steps are performed automatically (or manually when needed) by the algorithm created based on principles of particle swarm optimization (PSO) algorithm using Visual C#.

Experimental tests show that the segmentation design improves AM processes from the aspects of building time, material consumption and the surface quality. Segmentation design empowers users of AM technologies to reduce consumption of material by decreasing the support structures, to decrease the time of building by lowering the segments height and to decrease the surface roughness.

This paper presents an original approach in efficiency improvement of AM technologies, thus bringing the AM one step closer to maturity.

The purpose of this paper is to examine whether and how firm's agency costs played a role in the voluntary adoption of the eXtensible Business Reporting Language (XBRL) under the SEC's voluntary filing program (VFP) that encouraged the voluntary adoption of the XBRL.

This study employs a logistics regression and a sample of 140 firms that voluntarily participated in the VFP during its entire existence in the United States, and 140 matched-pair counterparts that did not voluntarily adopt the XBRL to investigate the role of agency costs in the voluntary adoption of XBRL-based financial reporting.

We find evidence consistent with the conjecture that a firm's low magnitude of agency costs plays a significant motivating role in the voluntary adoption of XBRL-based financial reporting. Our results continue to hold after using an alternative measure of agency costs and conducting two-stage least squares regressions. Supplementing these results, the study also shows that the level of agency costs of voluntary XBRL adopters remains statistically unchanged after the adoption while the level of agency costs associated with the firms that did not participate in SEC's VFP significantly decline after the adoption during the XBRL mandate.

The findings of this study suggest that based on a firm's level of agency costs, regulators and policymakers, especially those in countries that are yet to mandate XBRL reporting, can, in advance, identify firms that are more likely to comply with their new financial reporting initiatives.

This paper provides first evidence on the role of agency costs in the voluntary adoption of XBRL using data from the United States.