一谈及企业数字化，大部分的企业领导与员工都会想到那是技术的事儿，既然是技术在一些领导的眼里 感觉就很简单，无非就是买个软件、上个系统、找个技术团队开发一下，然后想当然的认为问题就解决 了，数字化就完成了。但问题是技术侧的水比想象中深得多，然比技术更深更复杂的是技术背后的认知 与思维变革。今天老杨不谈所谓的转型与变革，就通俗的从技术视角讲讲企业数字化的技术难点究竟有 哪些。 这个问题在企业信息部门的眼里看起来是再清楚不过了，可问题是信息部门无法将这些技术问题向高层 决策者完全阐明其背后的复杂性与长远影响，导致技术规划常被简化，专业的问题被弱化，最后企业又 不得不花费更多的时间和成本去弥补因初期认知不足带来的各种技术债，今天老杨就来总结一下数字化 技术侧的几个关键难点。 第一，技术选型如"赌博" 大部分的传统企业开始做数字化首要面对的问题就是究竟选择何种技术路线，可以说是技术路线如"赌 博"一场，稍有不慎便满盘皆输。不同的技术架构、开发语言、部署方式与生态适配，直接影响系统未 来的可扩展性与维护成本。比如一些企业盲目跟风选择热门技术栈，却忽视自身业务场景与团队能力， 导致系统上线即"瘫痪"，还比如一些企业没有任何 ...

智通财经APP获悉，据港交所12月29日披露，上海汉得信息技术股份有限公司(简称：汉得信息)向港交所主板提交上市申 请，国泰君安融资有限公司为其独家保荐人。 | 编纂 的编纂 数目 | | : [編纂]股H股(視乎]編纂]而定) | | --- | --- | --- | | 编纂 數目 | .. | [编纂]股H股(可予 编纂]) | | [编纂 數目 | : | [編纂]股H股(可予]編纂]及視乎[編纂]而定) | | 最高 编纂 : | | 每股H股[編纂]港元,另加1.0%經紀佣金、 | | | | 0.0027%證監會交易徵費、0.00565%香港 | | | | 聯交所交易費及0.00015%會財局交易徵費 | | | | (須於申請時以港元繳足,多繳款項可予退 | | | | 環) | | 面值 : | | 每股H股人民幣11.00l元 | | 網景 : | | 【編纂】 | 公司简介 招股书显示，汉得信息(300170.SZ)是中国领先的企业IT咨询与数字解决方案服务供应商。公司为大型及头部企业提供全 方位的数字化与智能化解决方案。凭借AI应用、自主产品及ERP实施服务，公司协助企业实现数字化 ...

智通财经APP获悉，据港交所12月29日披露，上海汉得信息技术股份有限公司(简称：汉得信息)向港交所主板提交上市申 请，国泰君安融资有限公司为其独家保荐人。 | | 编纂]的[编纂]數目:[编纂]股H股(視乎[編纂]而定) | | | --- | --- | --- | | [编纂]數目 | : | [编纂]股H股(可予 编纂]) | | 编纂 數目 | : | [編纂]股H股(可予]編纂]及視乎[編纂]而定) | | 最高 编纂 | .. | 每股H股[編纂]港元,另加1.0%經紀佣金、 | | | | 0.0027%證監會交易徵費、0.00565%香港 | | | | 聯交所交易費及0.00015%會財局交易徵費 | | | | (須於申請時以港元繳足,多繳款項可予退 | | | | 環) | | 面值 : | | 每股H股人民幣[1.00]元 | | [編纂] : | | 【编纂】 | 公司简介 招股书显示，汉得信息(300170.SZ)是中国领先的企业IT咨询与数字解决方案服务供应商。公司为大型及头部企业提供全 方位的数字化与智能化解决方案。凭借AI应用、自主产品及ERP实施服务，公司协助企业实现数字 ...

2025年即将进入尾声，这一年我们见证了技术浪潮的澎湃，也目睹与经历了企业数字化转型的艰辛与蜕 变。此时站在2025年的这个时间点回望，那些曾经模糊的路径正逐渐清晰，数字化已不再是选择题，而 是未来生存的必答题。2026年的企业数字化将迈向何方？为此老杨总结了2026年企业数字化的六大关键 词： 企业做数字化转型建设，价值是核心。但价值的实现一直是CIO们最为头疼的问题，老杨认为价值的实 现不仅是技术与业务的匹配，更需关注人在变革中的体验与感受。信息部门在数字化建设过程中传递的 情绪价值，正成为决定转型成败的关键隐形变量。要知道当新技术遭遇阻力、被质疑时，真正推动变革 的往往是信任、共情与成就感这些"软性"力量。因此信息部门在2026年要学会用温度赢得认同，以专业 建立信任，善用共情沟通化解抵触情绪，通过小步快跑的迭代方式让业务部门看见成效、获得成就感， 这就是情绪价值的体现。而情绪价值创造能力一直是信息部门的短板，也是2026年需重点补足的能力。 关键词一：十五五 十五五"规划的启航，将为企业数字化注入国家战略层面的强劲动力，是企业未来发展的指引灯塔。企 业数字化如何建才能体现价值，是CIO们一直头疼的问题 ...

Core Viewpoint - On December 16, 2023, Jia Mei Food Packaging (Chuzhou) Co., Ltd. announced a change in control as its controlling shareholder, China Food Packaging Co., Ltd., signed a share transfer agreement with Suzhou Zhuyue Hongzhi Technology Development Partnership (Limited Partnership) [1] Group 1: Share Transfer and Control Change - The share transfer agreement indicates that Zhuyue Hongzhi will acquire 279 million unrestricted shares from China Food Packaging at a price of 4.45 yuan per share, representing 29.90% of the total share capital [2] - Following the completion of the share transfer, Zhuyue Hongzhi will become the controlling shareholder, with Yu Hao, the founder of Chasing Technology, becoming the actual controller of Jia Mei Packaging [1][2] Group 2: Business Overview - Jia Mei Packaging operates as a full-chain service provider for beverage brands, offering research, design, production, and sales of various beverage packaging containers, along with beverage formula development and marketing services [2] - The company currently owns 17 subsidiaries, covering multiple sectors including tin printing, three-piece cans, two-piece cans, and various packaging materials for beverage filling [2] Group 3: Further Share Acquisition - Zhuyue Hongzhi plans to further increase its stake through a partial tender offer, aiming to acquire an additional 233 million shares, which accounts for 25.00% of the total share capital [3] - The tender offer includes commitments from existing shareholders to accept the offer for a total of 1.03 billion shares (11.02% of total share capital) from China Food Packaging, 890 million shares (9.53%) from Fuxin Investment, and 230 million shares (2.49%) from Zhongkai Investment [3]

格隆汇12月12日丨汉得信息(300170.SZ)在投资者互动平台表示，公司是企业数字化、智能化产品及解 决方案的综合服务供应商，产品及服务涵盖数智化软件产品、解决方案、咨询服务及实施交付，暂不涉 及传感器的研发与生产。 ...

格隆汇12月11日丨南网数字(301638.SZ)在投资者互动平台表示，公司暂未直接涉及通用量子计算机的 研发或技术输出。目前公司量子技术应用聚焦电力能源行业特定需求，公司已掌握电力量子传感器的设 计制造与应用关键技术。公司主营业务包括电网数字化、企业数字化和数字基础设施三大业务体系，其 中数字基础设施业务类别中的数据中心（IDC）业务包含算力投资、建设、运营服务，具体情况参见公 司招股说明书。 ...

Core Insights - The article discusses the impact of knowledge spillover on total factor productivity through digital transformation and agglomeration networks among companies [1][3][4] Group 1: Knowledge Spillover Metrics - Specialized knowledge spillover (SK_Spillover) is measured by the knowledge spillover effect from companies within the same industry located within a 50 km radius, indicating stronger effects with larger values [1][3] - Diversified knowledge spillover (DK_Spillover) is calculated similarly but includes companies from different industries within the same 50 km range [1][4] Group 2: Data and Sample Size - The study includes over 10,000 samples from 1,343 companies, with nearly 3,000 non-zero effective values for specialized knowledge spillover and over 10,000 for diversified knowledge spillover [1] - The data encompasses original data, calculation codes, and final results, allowing for verification of accuracy [1] Group 3: Mechanism Examination - The mechanism examination shows that digital transformation enhances the effectiveness of knowledge production and transfer among companies, facilitating rapid exchange of social information and knowledge [3][4] - The results indicate that both digital transformation and agglomeration networks significantly promote diversified knowledge spillover, with robust effects even after addressing endogeneity issues [4] Group 4: Yearly Knowledge Spillover Data - The data table presents yearly values for specialized and diversified knowledge spillover for two companies from 2014 to 2024, showing trends in knowledge spillover over the years [5]

Core Insights - The article discusses the impact of knowledge spillover on total factor productivity (TFP) in the context of digital transformation and agglomeration networks among companies [1][4]. Group 1: Knowledge Spillover Metrics - The study constructs two indicators: specialized knowledge spillover (SK_Spillover) and diversified knowledge spillover (DK_Spillover), based on the proximity of firms within a 50 km radius [1][4]. - SK_Spillover reflects the knowledge spillover effect from firms in the same industry, while DK_Spillover indicates the spillover from firms in different industries [1][4]. Group 2: Data and Methodology - The dataset includes over 10,000 samples from 1,343 companies, with raw data, calculation codes, and final results provided for verification [1]. - The methodology is based on the approach outlined in the journal "Management World" by Han Feng, focusing on the relationship between digitalization, agglomeration networks, and knowledge spillover [2]. Group 3: Mechanism Examination - The analysis shows that digital transformation enhances information dissemination and the effectiveness of knowledge production and transfer among firms [4][5]. - The results indicate that both specialized and diversified knowledge spillovers are positively influenced by digitalization and agglomeration networks, with robust effects observed even after addressing endogeneity issues [5]. Group 4: Empirical Results - The empirical data presented in the table shows trends in specialized and diversified knowledge spillover from 2014 to 2024, highlighting variations in spillover levels across different years [6].

Core Viewpoint - The article discusses the evolving landscape of e-commerce during the Double 11 shopping festival, highlighting the challenges faced by industry players and the potential role of Feishu in transforming operational efficiency through digital tools and AI integration [5][9][20]. Group 1: E-commerce Challenges - The e-commerce industry is experiencing a "midlife crisis," characterized by a decline in excitement and increased operational complexity, with the number of products in live streams ballooning to over 400, nearly double that of previous events [5][7]. - Despite the abundance of data, e-commerce companies struggle with high management costs and low decision-making efficiency, leading to a disconnect between data production and utilization [7][9]. - The rise of live commerce has compressed decision-making cycles, necessitating rapid adjustments to marketing strategies, which are hindered by fragmented data across multiple platforms [8][9]. Group 2: Feishu's Role - Feishu has entered the Double 11 preparations, positioning itself as a solution to the operational inefficiencies plaguing the e-commerce sector by offering integrated data management tools [5][11]. - The platform enables businesses to consolidate data from various sources, allowing for real-time analysis and decision-making, thus enhancing operational agility [9][11][20]. - Feishu's multi-dimensional spreadsheets serve as a "dashboard" for e-commerce teams, streamlining processes and reducing the need for manual data handling [9][11][22]. Group 3: AI Integration - The integration of AI tools within Feishu's platform allows for automation of repetitive tasks, significantly improving efficiency and freeing up human resources for more value-adding activities [15][20]. - Companies like Ato Star and Oupai Home have successfully implemented Feishu's solutions, resulting in substantial reductions in operational delays and improved management of live streaming events [22][23]. - The shift towards AI-driven processes is seen as a necessary evolution for the e-commerce industry, enabling teams to focus on creative and strategic tasks rather than mundane operational duties [20][29]. Group 4: Future of E-commerce - The article suggests that the future of e-commerce lies in embracing digital tools that enhance agility and responsiveness, moving away from traditional centralized systems [27][28]. - Feishu's approach exemplifies a "decentralized" model that empowers frontline employees to make decisions quickly, fostering a more dynamic organizational structure [27][29]. - The ongoing transformation in the e-commerce sector highlights the importance of continuous optimization and the need for businesses to adapt to rapidly changing market conditions [28][29].