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The paper aims to theoretically and experimentally investigate vibratory peg-bush alignment using elastic vibrations of the peg, when the peg is axially excited by a pressed piezoelectric vibrator on the upper end.

Experimental research of part alignment using elastic vibrations was performed and dependencies of alignment duration on excitation signal parameters and initial pressing force were defined for rectangular and circular cross-section parts. Mathematical model of two-mass dynamic systems with elastic contact model representing alignment process was created. Dependencies of system parameters on the alignment duration were obtained by numerically solving systems differential equations.

Theoretical and experimental investigation approved the usage of elastic vibrations for alignment of chamferless circular and rectangular cross-section parts. This novel method of part alignment compensates axial misalignment between mating parts by directional displacement of movably based bush.

Impact and non-impact interaction between bush and peg is possible; however, only non-impact regime was investigated. Static and dynamic coefficients of friction between the parts are equivalent and do not depend on relative velocity of parts.

The results are useful in designing reliable and effective assembly equipment with vibratory assistance alignment for peg-bush operations, which do not require auxiliary sensors and feedback systems. Use of a piezoelectric resonator for peg excitation makes this system easily adaptable to the existing automated assembly equipment.

The proposed method is a new approach to vibratory alignment. The data obtained during investigation expand the insight of the physical processes that drive bush to the axial alignment direction.

The purpose of this study is to provide a micro-nano chip automatic alignment system. Used for micron and nanometer channel alignment of microfluidic chip.

In this paper, combined with the reconstructed micro–nanoscale Hough transform theory, a “clamp–adsorb–rotate” chip alignment method is proposed. The designed alignment system includes a microscopic identification device, a clamping device and a suction device. After assembly, the straightness of the linear slide rail in the horizontal and vertical directions was tested, respectively. The results show that in the horizontal and vertical directions, the linearity error of the linear slide is +0.29 and 0.30 µm, respectively, which meets the requirement of chip alignment accuracy of 15 µm. In the direction of rotation, the angular error between the microchannel and the nanochannel is ±0.5°. In addition, an alignment flow experiment of the chip is designed. The results demonstrate that the closer the angle between the microchannel and the nanochannel is to 90°, the fluid fills the entire channel. Compared with the conventional method, the method and the assembly system realize fully automatic double-layer chip alignment.

A mechanical device designed by Hough transform theory can realize microfluidic chip alignment at nanometer and micron level.

The automatic alignment device adopts Hough transform principle and can be used for microfluidic chip alignment.

The paper aims to investigate theoretically and experimentally vibrational alignment of parts in an assembly position under kinematical excitement of the movably based part.

Presents developed mathematical model for vibrational alignment when the kinematical excitement of movable part is applied along the insertion axis. Dependencies of alignment duration on stiffness of basing elements and excitation frequency were defined numerically solving the mobile‐based part alignment equations. Alignment experiments of rectangular cross‐section and cylindrical parts under kinematical excitement were carried out.

The mathematical model and the experiments have demonstrated that alignment of the parts being assembled happens due to directed displacement of the movable part resulted by certain parameters of the system and excitement. In the course of the displacement, mating surfaces are aligned and the final mutual orientation of the parts before insertion is realized. Experiments have proved validity of the developed mathematical model. This process reduces allowable axial non‐coincidence and angular misfit of the parts to be assembled.

Impact and non‐impact regimes of the displacement exist depending on the excitement amplitude and initial contact force between the parts. Also, during the vibrational alignment it is possible to control dry friction force between parts by additional high frequency vibrations. Besides, the vibrational excitement can be not only harmonic, but also impulse, bi‐harmonic, etc. Only non‐impact regime of the motion without dry friction force control was investigated and presented in the paper.

The paper investigates the vibrational alignment method based on the directed vibrational displacement of the connecting part, which does not require high preciseness of the interdependent position of the parts in the assembly position.

Vibrational assembly devices of directional action enable compensation of errors of the parts' mutual positioning without use of sensors, feedback systems and control algorithms.

Drawing on the knowledge-based view, this study investigates how IT–business alignment influences business model design via organizational learning and examines the moderating role of data-driven culture in the relationship between IT–business alignment and business model design via organizational learning.

Using multi-respondent survey data collected from 597 Chinese firms, mediation and moderated mediation analyses were used to examine this study's hypotheses.

The mediation test results revealed organizational learning served as a mediator between IT–business alignment and two types of business model design (i.e. novelty- and efficiency-centered). In addition, data-driven culture strengthened the indirect effects of IT–business alignment on these two types of business model design via organizational learning.

This study extends current understandings of the relationship between IT–business alignment and business model design by revealing the mediating role of organizational learning and investigating its indirect effects under various degrees of data-driven culture. As such, it contributes to the literature on the business model and IT–business alignment and provides insights for managers seeking to achieve the expected business model design.

For the last four decades, the alignment of strategy and digital technology has persisted as one of the most critical and bothersome issues for senior government executives. Against this backdrop and drawing on the fruits of an extended program of collaborative research between 1995 and 2020, this chapter draws attention to how government organizations foster effective alignment and how this is achieved through four distinct cycles of alignment work. Considering that this work is heavily people- and organization-centric, the chapter calls for greater involvement of organization development and change scholars and practitioners in this important area of organizational life and work.

The purpose of this study is to provide a systematic literature review on taxonomy alignment methods in information science to explore the common research pipeline and characteristics.

The authors implement a five-step systematic literature review process relating to taxonomy alignment. They take on a knowledge organization system (KOS) perspective, and specifically examining the level of KOS on “taxonomies.”

They synthesize the matching dimensions of 28 taxonomy alignment studies in terms of the taxonomy input, approach and output. In the input dimension, they develop three characteristics: tree shapes, variable names and symmetry; for approach: methodology, unit of matching, comparison type and relation type; for output: the number of merged solutions and whether original taxonomies are preserved in the solutions.

The main research implications of this study are threefold: (1) to enhance the understanding of the characteristics of a taxonomy alignment work; (2) to provide a novel categorization of taxonomy alignment approaches into natural language processing approach, logic-based approach and heuristic-based approach; (3) to provide a methodological guideline on the must-include characteristics for future taxonomy alignment research.

There is no existing comprehensive review on the alignment of “taxonomies”. Further, no other mapping survey research has discussed the comparison from a KOS perspective. Using a KOS lens is critical in understanding the broader picture of what other similar systems of organizations are, and enables us to define taxonomies more precisely.

This paper presents an analytical framework for modeling and measuring strategic alignment. The resource-product-market (RPM) model is introduced as a means of representing the alignment of the firm's internal resources with its product lines and external markets. A strategic alignment index is defined to measure the degree of alignment represented by a model.

The RPM model is derived as an extension of prior research on diversification indexes. The strategic alignment index is mathematically defined and the properties of the model are characterized using graph theory. The approach is illustrated for two example firms.

The RPM model is flexible and can be used with different types and measures of resources, products and markets. The model represents strategy in a structural manner addressing a vertical type of alignment. The index ranges continuously from 0 to 1.0, providing a useful scale for measurement and comparison.

Practitioners may use RPM modeling to assess the current alignment of their respective firms and to identify strategic alternatives which increase alignment through a taxonomy of 13 strategic moves. The results of applying the model to ten firms are summarized.

The paper contributes to the literature by providing a new method for modeling firm strategy which integrates resource and industry views, thereby enabling a measurement of their alignment. The paper is also novel in the application of graph theory to management.

The purpose of this paper is to examine a recent comprehensive corporate real estate (CRE) alignment model which was derived from previous CRE alignment models. This study proposes several modifications and additions based on business and decision-making literature to increase the framework’s multidisciplinary strength and extend its implementation phase.

Literature from various fields is reviewed and “lessons” incorporated into the framework. The business literature review began with corporate strategy theories cited in CRE alignment theory and extended to critiques of those and more recent theories. Likewise, decision-making and implementation both began with material cited in CRE literature and “rippled” out to encompass pertinent material.

The model used provides a robust framework, and this study has identified several areas that would appear to improve that model from a theoretical and practical perspective. Areas of further research are identified that appear to offer opportunities to further develop the framework.

Historically, there has been a tendency for new CRE alignment models to be created rather than existing ones being developed further. Here, a framework derived from a meta-study of CRE alignment models is reviewed, and improvements are proposed to further develop CRE alignment theory and its application in practice through the addition of viewpoints from the business field and more focus on the implementation phase of the model.

Recent advancements in Artificial Intelligence (AI) and, at its core, Machine Learning (ML) offer opportunities for organizations to develop new or enhance existing capabilities. Despite the endless possibilities, organizations face operational challenges in harvesting the value of ML-based capabilities (MLbC), and current research has yet to explicate these challenges and theorize their remedies. To bridge the gap, this study explored the current practices to propose a systematic way of orchestrating MLbC development, which is an extension of ongoing digitalization of organizations.

Data were collected from Finland's Artificial Intelligence Accelerator (FAIA) and complemented by follow-up interviews with experts outside FAIA in Europe, China and the United States over four years. Data were analyzed through open coding, thematic analysis and cross-comparison to develop a comprehensive understanding of the MLbC development process.

The analysis identified the main components of MLbC development, its three phases (development, release and operation) and two major MLbC development challenges: Temporal Complexity and Context Sensitivity. The study then introduced Fostering Temporal Congruence and Cultivating Organizational Meta-learning as strategic practices addressing these challenges.

This study offers a better theoretical explanation for the MLbC development process beyond MLOps (Machine Learning Operations) and its hindrances. It also proposes a practical way to align ML-based applications with business needs while accounting for their structural limitations. Beyond the MLbC context, this study offers a strategic framework that can be adapted for different cases of digital transformation that include automation and augmentation of work.

While scholarly attention has mainly focused on team-level or relational constructs for the success of team performance, understanding the inter-play between these two streams of research remains limited in digital transformation projects. Borrowing from social exchange theory, this study aims to explore the antecedents of team alignment leading to team performance with mediation effects of trust, commitment and customer–service provider relationship. The moderating role of relationship length was also examined.

Data was collected using a survey of 180 employees working on digital projects in B2B context, mostly in the Indo-Pacific region, specifically Singapore, Indonesia, Malaysia and India. Partial least squares method with multi-group analyses and bootstrapping method were used to analyze the data.

Findings show that customer control and team capability are the strongest antecedents of team alignment, and inter-play between the customer–provider relationship with team-level constructs is also significant. Relationship length has higher level of moderation impact on trust–team performance link compared to commitment–team performance relationship.

The study considers moderation impact of relationship length on trust, commitment and team performance but not other constructs. Also, gender ratio is skewed in the data set.

Digital transformation practitioners need to be aware of relational constructs (not only team-level constructs) when designing successful long-term digitalization strategies for organizations.

This study is one of the first to document the inter-play between team alignment and relational constructs (such as trust, commitment, and customer–service provider relationship), with moderation impact of relationship length leading to team performance in digital transformation projects.