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The purpose of this paper is to develop and to empirically test a model that explains how managing differences between an information technology (IT) provider and an overseas client influences partnership quality and ultimately affects the continuity of the relationship.

A field survey by distributing questionnaires to Indonesian IT providers was conducted over four months, yielding 78 completed responses. These empirical data were analyzed by the partial least squares–structural equation modeling technique to examine the measurement and structural models.

Managing differences, i.e. cultural, temporal and standards differences, has a positive impact on partnership quality through inter-firm interaction, i.e. information exchange, coordination and participation. Partnership quality, consisting of the dimensions of commitment, trust and integration, has a substantial positive impact on the continuity of the relationship.

This study was limited by the use of a limited number of samples, reducing the precision of the results.

This study suggests that if the IT provider is able to manage the cultural, temporal and standards differences with the overseas client, it increases information exchange, coordination and participation between both parties, which are necessary for establishing a high-quality partnership.

This study is the first empirical examination of how the management of differences between an IT provider and an overseas client influences the continuity of their relationship through interaction and partnership quality.

The purpose of this paper is to design a research model and analyze the relationship between open innovation and cleaner production. The paper maps and characterizes the conditions of open innovation against cleaner production in Indonesian batik small and medium enterprise (SME), particularly in Java and Madura. The mapping process is executed by classifying the batik SME into four quadrants. The diagram is a quadrant in which there are four parts to distinguish each of the ability of batik SMEs in understanding and achieving cleaner production through open innovation. This research will obtain a new method or model that can be applied by organizations to achieve cleaner production through an open innovation. The data is obtained from 182 batik SMEs located in Laweyan, Madura and Lasem (in Java Island, Indonesia).

One of the problems in batik SME is the waste management from the dyeing and wax removal process. In the first stages of this research, a number of initial models were elaborated as a reference, then the results of the elaboration became a new research model. The research model that has been produced is then tested using data from respondents. Based on the test results, the model can be stated valid or not. In this study, the model is valid after testing data from 182 respondents, because all outer loading for all indicators is above 0.7. The composite reliability and AVE values of all constructs were above 0.7 and 0.5. Based on the validated research model, the data is statistically processed by using the Structural Equation Modeling (SEM). By using the SEM method and statistical software SMART PLS 3.0this research can be supported to achieve the research objectives.

Based on data testing and processing, open innovation climate could predict a sustained relationship to open innovation with an accuracy rate of 0.466 and influence rate of 0.427, whereas open innovation could predict a sustained relationship to cleaner production with an accuracy rate of 0.183 and influence rate of 0.324. The relationships between open innovation climate and open innovation; including open innovation toward cleaner production, are statistically significant because all prediction values and accuracy in the model have met the criteria for measurement parameters based on the value of R², p value and T-statistics to be stated as a significant relationship.

This research provides an overview of the influence and importance of open innovation in creating an environmentally friendly production process in the context of cleaner production. Cleaner production on batik SMEs can be achieved through open innovation, both for inbound open innovation and outbound open innovation. Open innovation comprehensively provides support for batik SMEs in achieving cleaner production. Open innovation can be run well and optimally if it gets support from a conducive climate open innovation. Furthermore, the implementation of cleaner production could be a guideline for the owner to minimize the waste from batik SME production, both for natural and synthetic dyes. Some limitations in these study include the absence of influence from the existing stakeholders on batik SMEs on the implementation process of open innovation; the use of the cross-sectional approach that results in the unavailability of further analysis regarding the dynamics or improvements that occur in attaining cleaner production through open innovation; and finally providing no analysis of the differences in characteristics at each location of batik SMEs.

The implementation of cleaner production model is considered as one of the new methods and references in conjunction with reducing the negative impact of waste toward the environment, particularly in the traditional textile industry which is limited in waste management capability.

Inspection for quality of product is performed mostly at the end of the production line. Therefore, non‐conformance is known at the time it is inspected. One solution is applying in or between process inspection. Moreover, in or between processes the required correction can be performed before parts are manufactured by the subsequent process. Compares two sequences of in‐process inspection and correction facilities. The first is where the correction is made concurrently with the process (reworking). The second involves establishment of a separate correction facility and therefore correction is performed separately (correcting). Uses process, inspection and correction costs as an economical measurement of accepted product for both sequences. On the other hand, an accepted product is not always perfectly on its target value, which will eventually result in loss to the customer. Uses a model of the sum of these costs and loss to determine the best sequence.

The purpose of this paper is to empirically evaluate the critical factors for successful quality engineering (QE) implementation in automotive-related companies in Malaysia and Indonesia. The existence of these critical factors for the successful application of QE would help the automotive industries, especially in Malaysia and Indonesia, to be able to investigate their current QE practices and how they could be improved.

Delphic hierarchy process (DHP) methodology is used in this study. The DHP method is a combination of the Delphi method and the analytic hierarchy process (AHP) approach for determining the ranking of the factors and sub factors needed for successful QE implementation. The Delphi method is employed to gather data from automotive experts in both countries and the AHP approach is used to rank the critical factors for success of QE practices.

The findings of this study showed that the automotive industries in Malaysia and Indonesia stressed the importance of management responsibility and people management for the successful implementation of QE. Strategic quality planning, continuous improvement, and technology- and production-related resources are the most important sub factors for successful QE in both countries.

The series of rounds that took place during the Delphi method increased the length of time required for data collection and the follow-up process. On the basis of the consideration given, the limited resources included time, financial resources, and technical availability for this study, which resulted in the small sample sizes used.

The ranking of the critical factors and sub factors for QE implementation could be useful for automotive-related companies in Malaysia and Indonesia to create action plans for improving their QE implementation.

The instrument that was developed is a contribution toward characterizing critical factors for QE. Using DHP methodology, nine factors and 31 sub factors have been validated through a series of rounds of the Delphi method. It was developed based on industry experts’ inputs. Therefore, the critical factors represent actual situation for QE success.